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9 Commits

Author SHA1 Message Date
a7eb35d29c chore(consistency): sync task status from DB [auto]
Updated by fix-consistency on 2026-06-22:
  - update .custodian-brief.md for feature-control
2026-06-22 23:21:38 +02:00
88f70d9505 Normalize agent instructions and workplan frontmatter (STATE-WP-0067)
- Align agent files with on-disk workplan prefixes (infer from workplan ids)
- Set workplan domain to registered domain_slug; add topic_slug where applicable
- Repair frontmatter delimiter formatting; migrate legacy task status literals
- Regenerate AGENTS.md, CLAUDE.md, and .claude/rules from State Hub templates
2026-06-22 23:16:24 +02:00
eb067c494c Add .repo-classification.yaml (CUST-WP-0050 T11 agent first-pass) 2026-06-22 17:47:36 +02:00
8528005bdb Complete WP-0003 T06 pilot validation and sync credential routing docs
Close the dangling MVP pilots task with H1 provider-switch test, pilot
validation report, and resolver tenant-override fix. Add credential routing
guidance to AGENTS.md and Claude rules.
2026-06-19 20:48:28 +02:00
82c7884103 Add capability registry scaffold and seed entries from reuse-surface
Bootstrap registry/indexes/capabilities.yaml and migrate helix_forge
capability entries owned by this repository for federation publishing.
2026-06-16 01:34:23 +02:00
fa39883aec First implementation 2026-06-15 00:42:14 +02:00
542d7c22be feat: set up new workplan FEATURE-WP-0004-feature-control-adoption-toolkit for consumer adoption support, guides, prompts, and agent/skill
- Builds on completed WP-0002 (canon alignment) and WP-0003 (MVP implementation).
- Tasks to formalize AdoptionGuide, reusable prompts, ConsumerBrief, initial skill/agent, repo docs updates, production path, and consumer workplan template.
- Follows exact AGENTS.md / ADR-001 conventions (frontmatter, task blocks, references to prior, protocol notes).
- Created per user request for next step in using feature-control for new projects.

All per session protocol.
2026-06-14 22:22:13 +02:00
afc0ef506b chore(consistency): sync task status from DB [auto]
Updated by fix-consistency on 2026-06-14:
  - update .custodian-brief.md for feature-control
2026-06-14 22:07:36 +02:00
f7f2502352 chore(consistency): sync task status from DB [auto]
Updated by fix-consistency on 2026-06-14:
  - update .custodian-brief.md for feature-control
2026-06-14 21:51:46 +02:00
37 changed files with 2352 additions and 61 deletions

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.claude/rules/agents.md Normal file
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## Kaizen Agents
Specialized agent personas available on demand via the state-hub MCP.
**Discover:** `list_kaizen_agents()` — returns all agents with name, description, category
**Load:** `get_kaizen_agent("tdd-workflow")` — returns full instructions; read and follow them
Common agents:
| Agent | Category | When to use |
|-------|----------|-------------|
| `tdd-workflow` | testing | Step-by-step TDD8 workflow for any feature |
| `code-refactoring` | quality | Code quality analysis and safe refactoring |
| `test-maintenance` | testing | Diagnose and fix failing tests |
| `requirements-engineering` | process | Prevent interface/mock mismatches upfront |
| `keepaTodofile` | process | Maintain TODO.md during work |
| `project-management` | process | Track status, determine next steps |
| `datamodel-optimization` | quality | Optimize dataclasses and data structures |
All 17 agents: call `list_kaizen_agents()` for the full list.

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## Architecture
<!-- TODO: Describe the key design decisions and component structure.
Key modules, data flows, external integrations, state machines, etc. -->
## Quick Reference
`~/state-hub/mcp_server/TOOLS.md` — MCP tool reference

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# Credential and access routing
**Audience:** Codex, Claude Code, Grok, and custodian agents that call **llm-connect**
for inference. Run this check **before** requesting secrets, API keys, SSH access,
login tokens, or database passwords — in any repo, not only `ops-warden`.
ops-warden **issues SSH certificates only** (`warden sign`, `cert_command`). Every
other credential need belongs to another subsystem. **Do not** message
`ops-warden` on State Hub expecting a secret value; the reply is a pointer, not a key.
### Lookup (do this first)
```bash
warden route find "<describe your need>" --json
warden route show <catalog-id> --json
```
Requires the `warden` CLI from `~/ops-warden` (`uv tool install .` or `uv run warden`).
| Agent runtime | How to orient |
| --- | --- |
| **Codex / Grok** (shell, HTTP State Hub) | `warden route` commands above; inbox `to_agent=feature-control` is for coordination, not secret vending |
| **Claude Code** (MCP when available) | `get_domain_summary("custodian")` for workstreams; **still** use `warden route` for credential ownership |
| **llm-connect** (inference service) | Never put secret retrieval in prompts; route custody to OpenBao/operator paths surfaced by `warden route` |
### Quick routing table
| I need… | Owner | ops-warden executes? |
| --- | --- | --- |
| SSH cert (`adm`/`agt`/`atm`) | ops-warden | **Yes**`warden sign` |
| API key, DB password, provider token | OpenBao (`railiance-platform`) | No — route only |
| Login / OIDC / MFA | key-cape / Keycloak | No — route only |
| Authorization decision | flex-auth | No — route only |
| activity-core → issue-core emission | activity-core + issue-core | No — `warden route show activity-core-issue-sink` |
| SSH tunnel | ops-bridge (+ `cert_command` from warden) | No — route only |
### Anti-patterns (do not do these)
- `POST /messages/` to `ops-warden` asking for `ISSUE_CORE_API_KEY`, `OPENROUTER_API_KEY`, etc.
- Inventing `warden secret`, `warden login`, `warden bao`, `warden tunnel` — they do not exist
- Pasting secrets into Git, State Hub, workplans, logs, or chat
### Other capabilities (reuse-surface)
Non-credential capabilities are usually discovered through **reuse-surface** federation
(`reuse-surface` registry / `capability.*` indexes). Credential routing is inlined in
every repo's agent instructions because it is high-frequency, high-risk, and easy to
get wrong.
**Canon:** `~/ops-warden/wiki/CredentialRouting.md` · catalog `~/ops-warden/registry/routing/catalog.yaml`

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## First Session Protocol
Triggered when `get_domain_summary("infotech")` shows **no workstreams**.
The project is registered but work has not yet been structured.
**Step 1 — Read, don't write**
- `~/the-custodian/canon/projects/infotech/project_charter_v0.1.md` — purpose, scope
- `~/the-custodian/canon/projects/infotech/roadmap_v0.1.md` — planned phases
- Scan repo root: README, directory structure, existing code or docs
**Step 2 — Survey in-progress work**
Look for TODOs, open branches, half-finished files. Note done vs. started but incomplete.
**Step 3 — Propose workstreams to Bernd**
Propose 13 workstreams — each a coherent strand, weeks to months, anchored to a
roadmap phase. **Wait for approval before creating.**
**Step 4 — Create workplan file first, then DB record (ADR-001)**
```
workplans/FEATURE-WP-NNNN-<slug>.md ← write this first
```
Then register in the hub:
```
create_workstream(topic_id="f39fa2a3-c491-414c-a91b-b4c5fcc6139c", title="...", owner="...", description="...")
create_task(workstream_id="<id>", title="...", priority="high|medium|low")
```
**Step 5 — Record the setup**
```
add_progress_event(
summary="First session: structured infotech into N workstreams, M tasks",
event_type="milestone",
topic_id="f39fa2a3-c491-414c-a91b-b4c5fcc6139c",
detail={"workstreams": [...], "tasks_created": M}
)
```
<!-- Delete or archive this file once past first session -->

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## Repo boundary
This repo owns **feature-control** only. It does not own:
<!-- TODO: List what belongs in adjacent repos, e.g.:
- SSH key management → railiance-infra/
- State hub code → state-hub/
-->

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**Purpose:** Open feature based multi-vendor, multi-tenant, multi-scope feature availability and provisioning engine.
**Domain:** infotech
**Repo slug:** feature-control
**Topic ID:** f39fa2a3-c491-414c-a91b-b4c5fcc6139c

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## Session Protocol
Dev Hub (State Hub API): http://127.0.0.1:8000
MCP server name in `~/.claude.json`: `dev-hub`
**Step 1 — Orient**
Read the offline-safe brief first — it works without a live hub connection:
```bash
cat .custodian-brief.md
```
Then call the MCP tool for richer cross-domain context when MCP tools are exposed:
```
get_domain_summary("infotech")
```
If MCP tools are unavailable in the current agent session, use the REST API:
```bash
curl -s "http://127.0.0.1:8000/state/summary" | python3 -m json.tool
```
If the hub is offline: `cd ~/state-hub && make api`
**Step 2 — Check inbox**
With MCP tools:
```
get_messages(to_agent="feature-control", unread_only=True)
```
Mark read with `mark_message_read(message_id)`. Reply or act on coordination
requests before proceeding.
Without MCP tools:
```bash
curl -s "http://127.0.0.1:8000/messages/?to_agent=feature-control&unread_only=true" \
| python3 -m json.tool
curl -s -X PATCH "http://127.0.0.1:8000/messages/<id>/read" \
-H "Content-Type: application/json" -d '{}'
```
**Step 3 — Scan workplans**
```bash
ls workplans/
```
For each file with `status: ready`, `active`, or `blocked`, note pending
`wait`/`todo`/`progress` tasks.
**Step 4 — Present brief**
1. **Active workstreams** for `infotech` — title, task counts, blocking decisions
2. **Pending tasks** from `workplans/` + any `[repo:feature-control]` hub tasks
3. **Goal guidance** — if `goal_guidance` in summary:
- `needs_workplan`: surface as top action — *"Repo goal '{title}' has no workplan yet"*
- `alignment_warnings`: flag if active work is not aligned with current goal
4. **Suggested next action** — highest-priority open item
5. **SBOM status** — flag if `last_sbom_at` is unset for this repo
If no workstreams: follow First Session Protocol (`first-session.md`).
**During work:** `record_decision()` · `add_progress_event()` · `resolve_decision()`
> State Hub is a *read model*. Bootstrap tools (`create_workstream`, `create_task`)
> are First Session Protocol only. Work structure belongs in repo files (ADR-001).
**Session close:**
With MCP tools:
```
add_progress_event(summary="...", topic_id="f39fa2a3-c491-414c-a91b-b4c5fcc6139c", workstream_id="<uuid>")
```
Without MCP tools:
```bash
curl -s -X POST http://127.0.0.1:8000/progress/ \
-H "Content-Type: application/json" \
-d '{"topic_id":"f39fa2a3-c491-414c-a91b-b4c5fcc6139c","workstream_id":"<uuid>","event_type":"note","summary":"what changed","author":"codex"}'
```
If workplan files were modified, ensure the local copy is up to date first:
```bash
git -C <repo_path> pull --ff-only
cd ~/state-hub && make fix-consistency REPO=feature-control
```
For repos where implementation runs on a remote machine (e.g. CoulombCore),
use the combined target which pulls before fixing:
```bash
cd ~/state-hub && make fix-consistency-remote REPO=feature-control
```
**C-15** (DB task ahead of file) is normal in multi-machine workflows — writeback
will sync the file to match DB. **C-16** (repo behind remote) blocks all writes
until you pull — intentional to prevent clobbering remote progress.

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## Stack
<!-- TODO: Fill in language, frameworks, and key dependencies -->
- **Language:**
- **Key deps:**
## Dev Commands
```bash
# TODO: Fill in the standard commands for this repo
# Install dependencies
# Run tests
# Lint / type check
# Build / package (if applicable)
```

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## Workplan Convention (ADR-001)
File location: `workplans/FEATURE-WP-NNNN-<slug>.md`
ID prefix: `FEATURE-WP-`
Work items originate as files in this repo **before** being registered in the hub.
Canonical workplan/workstream frontmatter statuses are:
`proposed`, `ready`, `active`, `blocked`, `backlog`, `finished`, `archived`.
Use `proposed` for a newly drafted plan, `ready` after review against current
repo state, and `finished` when implementation is complete. `stalled` and
`needs_review` are derived health labels, not stored statuses.
Closed workplans may be moved to `workplans/archived/` with a completion-date
prefix: `YYMMDD-FEATURE-WP-NNNN-<slug>.md`. The frontmatter id remains
unchanged; the prefix is only for quick visual reference.
Small opportunistic tasks discovered during another session use **Ad Hoc Tasks**:
`workplans/ADHOC-YYYY-MM-DD.md`, workstream slug `adhoc-YYYY-MM-DD`, and task ids
`ADHOC-YYYY-MM-DD-T01`, `T02`, etc. Use adhocs only for low-risk work completed
directly. Promote anything requiring analysis, design, approval, dependencies, or
multiple planned phases into a normal workplan.
Ecosystem todos from other agents arrive as `[repo:feature-control]` hub tasks —
visible at session start. Pick one up by creating the workplan file, then registering
the workstream.
Task blocks use this shape:
```task
id: FEATURE-WP-NNNN-T01
status: wait | todo | progress | done | cancel
priority: high | medium | low
state_hub_task_id: "<uuid>" # written by fix-consistency — do not edit
```
Status progression is `todo``progress``done`; use `wait` for waiting or
blocked work and `cancel` for stopped work.
<!-- Ralph Loop rules and HEUREKA sequence: ~/.claude/CLAUDE.md — do not duplicate here -->

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<!-- custodian-brief: generated by fix-consistency — do not edit manually -->
# Custodian Brief — feature-control
**Domain:** helix_forge
**Last synced:** 2026-06-14 19:48 UTC
**Domain:** infotech
**Last synced:** 2026-06-22 21:21 UTC
**State Hub:** http://127.0.0.1:8000 *(adjust if running on a remote machine)*
## Active Workstreams
### First implementation MVP: core feature-control using scored UseCaseCatalog and helix-forge standard
Progress: 0/6 done | workstream_id: `d261227d-9f2a-406e-88c3-80428ea33f23`
**Open tasks:**
- ► Implement OpenFeature wrapper and EvaluationContext builder `0952f00c`
- · Canonical feature registry (Git + metadata) `d90db732`
- · Multi-scope resolver with EvaluationScope and signals `e2ba2f41`
- · Local/test provider and adoption kit `857b7f25`
- · Governance basics: lifecycle, audit, explanation `c0174862`
- · MVP pilots and validation `78ddfd70`
*(none — repo may need first-session setup)*
---
## MCP Orientation (when available)
If the state-hub MCP server is reachable, call:
`get_domain_summary("helix_forge")`
`get_domain_summary("infotech")`
This provides richer cross-domain context.
If the MCP call fails, use this file as your orientation source.

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.repo-classification.yaml Normal file
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repo_classification:
standard: Repo Classification Standard
version: '1.0'
classified_at: '2026-06-22'
classified_by: agent
category: project
domain: infotech
secondary_domains: []
capability_tags: []
business_stake:
- technology
- product
- operations
business_mechanics:
- coordination
- operation

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@@ -4,7 +4,7 @@
**Purpose:** Open feature based multi-vendor, multi-tenant, multi-scope feature availability and provisioning engine.
**Domain:** helix_forge
**Domain:** infotech
**Repo slug:** feature-control
**Topic ID:** `f39fa2a3-c491-414c-a91b-b4c5fcc6139c`
**Workplan prefix:** `FEATURE-WP-`
@@ -101,19 +101,62 @@ curl -s -X PATCH "http://127.0.0.1:8000/tasks/<task_id>" \
---
## Local Developer Workflow
## Credential and access routing
This repository is documentation- and planning-focused (no source code, no traditional build/test/lint/install/run toolchain).
**Audience:** Codex, Claude Code, Grok, and custodian agents that call **llm-connect**
for inference. Run this check **before** requesting secrets, API keys, SSH access,
login tokens, or database passwords — in any repo, not only `ops-warden`.
**Verification and development commands (add to future sessions as needed):**
- Orient and review: `cat .custodian-brief.md` ; `cat INTENT.md SCOPE.md AGENTS.md README.md` ; `ls workplans/`
- Check hub state (requires local state-hub API): use the curl commands documented in "State Hub Integration" and "Session Protocol" sections above.
- After any workplan or doc changes: From `~/state-hub` checkout, run `make fix-consistency REPO=feature-control` (syncs markdown task statuses into hub DB, updates brief, populates state_hub_* IDs).
- Update task status in workplan files (use search_replace or equivalent) then re-run fix-consistency.
- Log required progress: `curl -s -X POST http://127.0.0.1:8000/progress/ ...` (see protocol).
- To verify changes post-fix: Re-`cat .custodian-brief.md`, re-`ls workplans/`, re-check task statuses in files vs hub queries, confirm no drift.
ops-warden **issues SSH certificates only** (`warden sign`, `cert_command`). Every
other credential need belongs to another subsystem. **Do not** message
`ops-warden` on State Hub expecting a secret value; the reply is a pointer, not a key.
No `make install`, `make test`, `make lint`, `make build`, or `make run` apply yet (pure docs repo). If implementation artifacts (e.g. OpenFeature wrappers, providers, or example code) are added later, define and document the appropriate commands here and in relevant workplans.
### Lookup (do this first)
```bash
warden route find "<describe your need>" --json
warden route show <catalog-id> --json
```
Requires the `warden` CLI from `~/ops-warden` (`uv tool install .` or `uv run warden`).
| Agent runtime | How to orient |
| --- | --- |
| **Codex / Grok** (shell, HTTP State Hub) | `warden route` commands above; inbox `to_agent=feature-control` is for coordination, not secret vending |
| **Claude Code** (MCP when available) | `get_domain_summary("custodian")` for workstreams; **still** use `warden route` for credential ownership |
| **llm-connect** (inference service) | Never put secret retrieval in prompts; route custody to OpenBao/operator paths surfaced by `warden route` |
### Quick routing table
| I need… | Owner | ops-warden executes? |
| --- | --- | --- |
| SSH cert (`adm`/`agt`/`atm`) | ops-warden | **Yes** — `warden sign` |
| API key, DB password, provider token | OpenBao (`railiance-platform`) | No — route only |
| Login / OIDC / MFA | key-cape / Keycloak | No — route only |
| Authorization decision | flex-auth | No — route only |
| activity-core → issue-core emission | activity-core + issue-core | No — `warden route show activity-core-issue-sink` |
| SSH tunnel | ops-bridge (+ `cert_command` from warden) | No — route only |
### Anti-patterns (do not do these)
- `POST /messages/` to `ops-warden` asking for `ISSUE_CORE_API_KEY`, `OPENROUTER_API_KEY`, etc.
- Inventing `warden secret`, `warden login`, `warden bao`, `warden tunnel` — they do not exist
- Pasting secrets into Git, State Hub, workplans, logs, or chat
### Other capabilities (reuse-surface)
Non-credential capabilities are usually discovered through **reuse-surface** federation
(`reuse-surface` registry / `capability.*` indexes). Credential routing is inlined in
every repo's agent instructions because it is high-frequency, high-risk, and easy to
get wrong.
**Canon:** `~/ops-warden/wiki/CredentialRouting.md` · catalog `~/ops-warden/registry/routing/catalog.yaml`
<!-- REPO-AGENTS-EXTENSIONS -->
<!-- Append repo-specific agent instructions below this marker.
The state-hub template sync preserves content after this line. -->
---
## Workplan Convention (ADR-001)
@@ -138,7 +181,7 @@ anything needing analysis, design, approval, dependencies, or multiple phases.
id: FEATURE-WP-NNNN
type: workplan
title: "..."
domain: helix_forge
domain: infotech
repo: feature-control
status: proposed | ready | active | blocked | backlog | finished | archived
owner: codex

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CLAUDE.md Normal file
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# feature-control — Claude Code Instructions
@SCOPE.md
@.claude/rules/repo-identity.md
@.claude/rules/session-protocol.md
@.claude/rules/first-session.md
@.claude/rules/workplan-convention.md
@.claude/rules/stack-and-commands.md
@.claude/rules/architecture.md
@.claude/rules/repo-boundary.md
@.claude/rules/credential-routing.md
@.claude/rules/agents.md

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# Consumer Brief: Feature-Control (for Adopting Repositories)
**Status:** Draft (expanded from canon-interface-card.md post WP-0003)
**Date:** 2026-06-14
**Modeled on:** info-tech-canon/infospace/agent/briefs/consumer-brief.template.md and interface-card.schema.yaml (per canon practices).
**Purpose:** Reusable brief for any consuming repo adopting feature-control. Use in State Hub, ralph sessions, or as attachment to adoption workplans.
## Project Identity
- **Producer:** feature-control (helix_forge domain)
- **Consumer:** [Insert your repo slug/project, e.g., "my-new-saas-app"]
- **Relationship:** Low-impact integration for feature availability control.
## Produced Concepts (What feature-control Provides)
- Thin OpenFeature wrapper + EvaluationContext builder (canon projections).
- FeatureRegistry (Git-backed FeatureDefinition with lifecycle/ownership).
- Resolver + FeatureDecision (EvaluationScope, multi-signal composition, rich explainability).
- LocalProvider (for dev/tests; extensible to real OF providers).
- Scored UseCaseCatalog (MVP/Architecture-Driving views per helix-forge standard).
- Canon-aligned terminology (EvaluationScope, Feature as ProducerCapability extension; explicit ITC-ORG/ACCESS/LAND/GOV mappings).
- Pilots, examples, and adoption guide (for quick start).
## Consumed Concepts (from InfoTechCanon and Related)
- ITC-ORG: Actor, Agent, Membership, Ownership, Tenant/Org patterns.
- ITC-ACCESS: Entitlement, Grant, AuthorizationDecision (signals only; not replaced).
- ITC-LAND: Environment, Deployment, Service, Repository, RuntimeResource.
- ITC-GOV: Decision, Control, Evidence, Policy, ProducerCapability, PurposeFit, ScopePressure.
- ITC-TaggingStandard: Feature categories.
- ITC-TASK: Lifecycle reviews/remediation.
- OpenFeature spec: EvaluationContext, FlagEvaluationDetails (reason/variant/metadata), provider model, safe defaults.
- (See docs/canon-mapping.md for full table with ownership/gaps.)
## Consumer Purposes / Demand
- Low-impact adoption for repos (human + agentic devs): Minimal code changes, typed keys, local tests, no backend lock-in.
- Multi-scope control: Tenant, agent, environment, domain, etc. (via EvaluationScope).
- Operational safety and cost control: Kill switches, degraded modes, compute path disabling.
- Governance and explainability: Lifecycle metadata, decision explanations, audit.
- Agent capability gating (with separate tool auth).
- Backend reversibility and GitOps (declarative registry + runtime overrides).
## Scope Pressure / Fit
- Current pain in consumer: [Insert: e.g., "ad-hoc booleans, tenant-specific code, flag debt, expensive paths running unnecessarily, unclear agent controls"].
- How feature-control helps: Canonical model, OF surface, scored UCs for prioritization, canon mappings for interoperability.
- Fit with consumer INTENT/SCOPE: [Insert mapping; e.g., "Your 'user can do X' maps to feature key 'your.domain.x'; tenant controls align with your multi-tenant model."]
## Produced Artifacts / Interfaces (for Consumer)
- SDK: feature-control-sdk (Python; thin client + providers + registry + resolver).
- Docs: AdoptionGuide.md, scored UCC, canon-mapping.md, mvp_pilot.py, sdk-examples/.
- Registry baseline: features.json (Git-committed FeatureDefinitions).
- Consumer brief template: This file (adapt for your project; attach to your workplans/brief).
## In Scope for This Consumer Adoption
- Integration of SDK/wrapper + context + evaluations.
- Feature registration and basic governance.
- Local/dev adoption + pilot validation.
- Mapping of your features to the scored UCC for MVP selection.
## Out of Scope (for Initial Adoption)
- Full production backends/adapters (deferred per WP-0003 scores).
- Deep entitlement self-service or complex approvals.
- Non-Python implementations (adapt the concepts via OpenFeature).
## Open Questions / Risks for Consumer
- [Insert project-specific: e.g., "How to export generated keys for our TypeScript frontend? Backend choice for production?"]
- General: See WP-0003 open questions (backend, generated keys, etc.).
## Evidence / Next Steps
- Pilot your adoption using docs/pilots/mvp_pilot.py (adapt for your UCs).
- Create consumer workplan (e.g., "Adopt feature-control") with tasks from the AdoptionGuide.
- Validate: Low effort, explainable decisions, scoped control, no backend dep.
- Contribute back: New UCs, patterns, or canon extensions via State Hub.
**Attach this (customized) to your project's .custodian-brief.md, workplans, or adoption sessions for traceability.**
See the full FeatureControlAdoptionGuide.md for step-by-step instructions and the reusable agent prompt. This brief ensures alignment with canon consumer practices (purpose-fit, scope pressure, interface cards).
Ready for your specific project? Provide details and we'll customize/generate the artifacts.

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# Feature-Control Adoption Guide for Consuming Repositories
**Status:** Draft (post WP-0003 MVP)
**Date:** 2026-06-14
**Audience:** Developers, architects, and AI agents integrating feature-control into new or existing projects (consuming repos).
**Based on:** FEATURE-WP-0003 MVP implementation, scored UseCaseCatalog.md, canon-mapping.md, canon-interface-card.md (modeled on info-tech-canon consumer briefs), pilot examples, PRD/INTENT boundaries.
This guide provides a practical, step-by-step process for adopting the feature-control framework. It ensures low-impact integration, canon alignment (EvaluationScope, ITC-ORG/ACCESS/LAND/GOV mappings), and use of the scored use cases for prioritization.
## 1. Prerequisites and Orientation
Before starting:
- Read the core docs in this repo (or the feature-control package):
- [INTENT.md](../INTENT.md): Stable intent, boundaries (OpenFeature-first, no auth/entitlement ownership, GitOps + runtime).
- [specs/ProductRequirementsDocument.md](../specs/ProductRequirementsDocument.md): Requirements, data models, architecture.
- [specs/UseCaseCatalog.md](../specs/UseCaseCatalog.md): Full catalog **with scoring applied per helix-forge UseCaseScoringStandard.md**. Use the summary table, MVP/Prototype/Architecture-Driving views to prioritize (e.g., high Value + low-moderate Cost for early adoption).
- [docs/canon-mapping.md](../docs/canon-mapping.md): Explicit mappings (e.g., Feature → ProducerCapability extension; EvaluationScope → ITC-ORG Membership + ITC-LAND dims). Avoid redefining canon terms.
- [docs/canon-interface-card.md](../docs/canon-interface-card.md): High-level consumer view (produced concepts, consumed ITC models, purposes, scope pressure).
- [docs/pilots/mvp_pilot.py](../docs/pilots/mvp_pilot.py) and [docs/sdk-examples/](../docs/sdk-examples/): Concrete usage examples.
- Understand key canon-aligned concepts:
- **EvaluationScope / TargetingScope**: Replaces bare "scope" (platform, tenant, agent, etc.). Maps to Memberships + Landscape resources.
- **FeatureDecision**: Rich (value, reason, source, scope, etc.) for explainability.
- **Context**: Projection from ITC-ORG (actors/agents), ITC-LAND (services/envs), ITC-ACCESS signals.
- Check your project's alignment with INTENT boundaries (mechanism over policy; overlay before mutation; capability-aware adapters).
**Read the brief for the target project** (`.custodian-brief.md`) and its AGENTS.md/INTENT.md to map your features to the scored UCC.
## 2. High-Level Adoption Flow (Based on Scored UCC)
Follow the recommended workflow from the helix-forge standard (capture → normalize → classify → score → select → implement). Prioritize from the UCC summary:
**MVP Candidates (strong for first integration, per scoring):**
- UC-A1: Adopt in new repo (core path; high user/business/strategic/proof value).
- UC-A2: Local/test provider (high proof/learning; low effort).
- UC-C1: Enable for tenant (multi-tenant control).
- UC-D3: AI agent capability (agent-first class).
- UC-E1: Disable compute-heavy per tenant (cost governance).
- UC-E4: Emergency kill switch (operational safety).
- UC-G1: Register with lifecycle (governance/hygiene).
**Supporting/Prototype:**
- UC-G3: Explain decision (explainability core).
- UC-H1: Provider switch (reversibility).
**Later/Enhancement:** Complex self-service, full analytics (lower urgency or higher cost per scores).
**Architecture Drivers (implement early for understanding, even if deferred):** Those with high Architecture Score (cross-repo, canon impact, policy, reuse, compute, observability) — e.g., A1, E1, D3, G1.
## 3. Step-by-Step Integration (Low-Impact, per UC-A1/A2)
1. **Add the SDK**:
- For Python projects: Add `feature-control-sdk` as a dependency (current: local via `pip install -e` from this repo's pyproject.toml; future: PyPI).
- Minimal: Copy `src/feature_control_sdk/` into your project initially.
- Optional: `openfeature-sdk` for real providers (backend-agnostic per design).
2. **Initialize the Client** (thin wrapper):
```python
from feature_control_sdk import FeatureControlClient, LocalProvider, FeatureRegistry, Resolver
client = FeatureControlClient(domain="your-service") # Optional OF domain
```
3. **Set up for Dev/Tests (LocalProvider, no backend)**:
```python
local_values = {
"your.domain.capability.feature": True, # Use canonical keys
# Simulate overrides/signals
"tenant:acme:your.feature": False,
"kill:your.feature": False,
}
client.set_provider(LocalProvider(local_values))
# For rich feature-control logic (MVP mode, no full OF needed):
reg = FeatureRegistry("features.json") # Git-committed baseline
# (Populate from registry or hardcode for pilot)
resolver = Resolver(reg, local_values)
client.set_resolver(resolver)
```
4. **Build Evaluation Context** (canon-aligned):
Use the `_build_context` logic or manual dict. Project from your system's facts (users, tenants, agents, services):
```python
context = {
"targeting_key": "user-123", # Per OF spec
"actor_type": "human", # or "agent"
"tenant_id": "acme",
"domain_id": "your-domain",
"agent_id": "my-agent-v1" if agent else None,
"environment": "production",
"service": "your-service",
"roles": ["user"],
"plan": "premium",
# Signals
"entitlement": True, # From your entitlement system (ITC-ACCESS)
}
```
5. **Evaluate Features** (standard OF surface + rich control):
```python
enabled = client.get_boolean_value(
"your.domain.capability.feature", # Canonical key (from registry)
default=False,
context=context
)
# For rich explain (UC-G3):
decision = client.explain("your.domain.capability.feature", False, context)
print(decision.reason, decision.scope) # e.g., "tenant_policy", "tenant:acme"
```
6. **Register Features (Governance, per UC-G1)**:
- Maintain a `features.json` (or registry export) in Git as declarative baseline.
- Example definition (matches PRD/UCC):
```json
{
"feature_key": "your.domain.capability.feature",
"name": "Your Capability",
"description": "...",
"owner": "your-team", # ITC-ORG
"category": "release", # ITC-Tagging
"default_value": false,
"safe_fallback": false,
"lifecycle_state": "active",
"expected_lifetime": "long_lived",
"tenant_configurable": true,
"documentation": "docs/features/..."
}
```
- Use `FeatureRegistry` to load/validate/register (enforces owner, temp review dates).
- In consuming code: Import or discover keys (stub scanner for UC-A3).
7. **Test and Adopt**:
- Use LocalProvider for unit/integration tests (deterministic, network-free; UC-A2).
- Pilot your features using `docs/pilots/mvp_pilot.py` as template (adapt for your UCs).
- Measure: Adoption effort (should be <1 small task), explainability, control without redeploys.
- For real providers: Configure OF provider (e.g., Unleash adapter) behind the client (H1 support).
8. **Governance and Advanced**:
- Enforce lifecycle in your registry (temp features get Tasks per ITC-TASK).
- Use `explain()` for support/debug (UC-G3).
- Audit changes (stub in pilot; expand per G4).
- For agents: Pass `actor_type: "agent"` + `agent_id` in context (D3 support; still enforce tool auth per boundaries).
## 4. Mapping Your Project's Features
- Review your project's INTENT/SCOPE/UCC (or equivalent).
- Map to feature-control UCC: E.g., "user can do X" → feature key like `your.domain.x` (per FR-3 naming).
- Score/prioritize using the standard (or copy from our scored UCC).
- Start with high-MVP-fit: Adoption + 2-3 core controls (tenant/agent/compute/kill).
- Register in your Git baseline; control via context (tenant_id for multi-tenant, agent_id for AI).
## 5. Common Pitfalls and Boundaries (from INTENT/PRD)
- **Do not** use features for auth (FR-8): Always pair with your authz system.
- **Do not** confuse with entitlement: Feature control composes but doesn't own (UC-F1).
- Client-side never enforces security.
- Start with local provider; add real backends later (backend-agnostic).
- Commit `features.json`/registry to Git for GitOps baseline.
## 6. Validation and Next Steps
- Run the adapted pilot: End-to-end for your MVP UCs.
- Check: Decisions explainable? Controls per scope (no cross-tenant)? Tests without backend?
- Metrics: Adoption time, decision coverage, compute savings.
- If it fits: Proceed to production hardening (e.g., real providers, full audit, adapter contracts).
- Report back: Update your project's docs/brief with adoption status. Consider contributing patterns back (e.g., new UCs or canon extensions).
## 7. Agent/AI Support Prompts and Skills
**Reusable Prompt Template** (for Grok, Claude, Cursor, etc.; copy-paste into your agent):
```
You are an expert at adopting the feature-control framework (OpenFeature-based, canon-aligned multi-scope feature availability control from the feature-control repo).
Follow this exact step-by-step guide from docs/FeatureControlAdoptionGuide.md:
[PASTE THE FULL GUIDE ABOVE]
For the current project (describe briefly: [e.g., "a new multi-tenant SaaS app in Python with user/engine/agent actors, compute-heavy features, need for tenant/agent controls"]):
1. Identify 5-10 candidate features from the project's scope/intent.
2. Map them to the scored UseCaseCatalog.md (prioritize MVP/Architecture-Driving).
3. Propose canonical feature keys (per naming convention).
4. Generate the integration code: client setup, context builder (using canon projections), evaluations, registry definitions (in JSON), tests with LocalProvider.
5. Create a simple pilot script adapted from mvp_pilot.py.
6. Note any canon gaps or custom UCs.
7. Ensure compliance with INTENT boundaries.
Output: Updated code diffs, new files (e.g., feature_flags.py, features.json, tests), and a brief adoption report referencing the scoring and canon-mapping.
```
**Dedicated Skill/Agent Recommendation**:
- **Yes, create one**: A "feature-control-adopter" skill or ralph-style prompt.
- Example skill file (add to your agent's skills dir or `docs/skills/adopt-feature-control.md`):
- Trigger: "adopt feature-control in this project" or "/adopt-fc".
- Behavior: Load this guide + canon-mapping + scored UCC + pilot as context. Walk user/agent through steps, generate code, validate against acceptance.
- For ralph-workplan users: Tie a consumer workplan (e.g., "Adopt feature-control") to this prompt.
- Enhancement: Integrate with State Hub (e.g., new workplan for consumer adoption in a target repo, using get_domain_summary for context).
- This repo can host the canonical version; consumers copy/adapt.
## 8. Gaps and Future Support (from WP-0003 Open Questions)
- Full backend providers (Unleash/Flagsmith adapters) and production config.
- Generated constants/key discovery (beyond stub).
- Deeper entitlement integration and tenant self-service.
- Full adapter contracts (for non-Python or custom backends).
- Publishing the SDK (PyPI, versioning).
- More pilots/examples for other languages/UCS.
**Next Step Recommendation**:
- If you have a specific new project/repo in mind (e.g., "my-new-app"), tell me the path or details — we can run a guided adoption session using the prompt above, generate the exact files, and create a consumer workplan (e.g., MYAPP-WP-0001-adopt-feature-control).
- Create a new workplan here (FEATURE-WP-0004-feature-control-adoption-toolkit) to formalize the guide, skill, and consumer brief.
- Expand the canon-interface-card.md into a full ConsumerBrief.md (per info-tech-canon templates).
This makes feature-control immediately usable for new projects while providing the requested guides/prompts/skills. The MVP gives a working foundation; we can iterate based on real adoption feedback.
Ready to proceed with a specific project or create the new artifacts? Provide details! (We'll log progress and sync via State Hub.)

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# MVP Pilot Validation Report (FEATURE-WP-0003-T06)
**Date:** 2026-06-19
**Pilot:** `docs/pilots/mvp_pilot.py`
**Tests:** `tests/test_registry_resolver.py`, `tests/test_sdk_wrapper.py` (incl. UC-H1)
## Scope
End-to-end validation of the WP-0003 MVP against the scored UseCaseCatalog MVP selection.
## Use cases exercised
| UC | Description | Result |
|----|-------------|--------|
| UC-G1 | Register with lifecycle | Pass — registry validates owner, temp review_date |
| UC-A1/A2 | Adopt with wrapper + local provider | Pass — thin client + LocalProvider, no backend |
| UC-C1 | Tenant enable | Pass — `tenant.preview` scoped to `acme` vs `globex` |
| UC-D3 | Agent capability | Pass — `agent.extract` evaluated with agent context |
| UC-E1 | Compute disable per tenant | Pass — `compute.heavy_ocr` disabled for tenant |
| UC-E4 | Emergency kill switch | Pass — kill signal overrides tenant/default at runtime |
| UC-G3 | Explain decision | Pass — `client.explain()` returns reason/source/scope |
| UC-H1 | Provider switch | Pass — `test_h1_provider_switch_without_business_code_change` |
## Observations
- **Adoption effort:** Single-script pilot; a consuming repo can integrate in one small task using the SDK + LocalProvider pattern (aligns with UC-A1 scoring).
- **Explainability:** Decisions include `reason`, `source`, `scope` — sufficient for MVP governance (UC-G3).
- **Runtime control:** Kill switch and tenant overrides applied without redeploy (local values mutated in-process).
- **Compute savings:** Pilot demonstrates disable path; real savings measurement deferred to production adapter work.
- **Canon alignment:** Evaluation uses tenant/agent context dimensions consistent with `docs/canon-mapping.md` (EvaluationScope).
## Fit vs scored catalog
The MVP UCs selected in WP-0003 (A1, C1, D3, E1, E4, G1, G3, H1) are all demonstrated. Deferred items from the catalog remain appropriate for follow-on work:
- Full tenant self-service (higher cost/risk)
- Experimentation analytics
- Complex approval workflows
- Production backend adapters (Unleash/Flagsmith/flagd)
No catalog adjustments required for the MVP boundary.
## Ready for next workplan
Pilot and automated tests satisfy T06 acceptance. Recommended follow-ons (per WP-0004 Production Hardening section):
1. Real OpenFeature provider adapters
2. Entitlement signal integration depth
3. SDK packaging (PyPI) and multi-language examples
4. Adoption validation in a real consuming repository

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"""
MVP Pilot script for WP-0003 T06.
Demonstrates core MVP UCs using the implemented components:
- UC-G1: register with lifecycle
- UC-A1/A2: adopt with wrapper + local
- UC-C1: tenant enable
- UC-D3: agent capability
- UC-E1: compute disable per tenant
- UC-E4: kill switch
- UC-G3: explain decision
Run: PYTHONPATH=src python3 docs/pilots/mvp_pilot.py
Shows no redeploy for changes, explainable decisions, canon alignment.
"""
from feature_control_sdk import (
FeatureControlClient,
LocalProvider,
FeatureDefinition,
FeatureRegistry,
Resolver,
)
print("=== MVP Pilot: feature-control core ===\n")
# 1. Registry (UC-G1)
reg = FeatureRegistry("/tmp/features.json") # "git" baseline
reg.register(FeatureDefinition(
feature_key="compute.heavy_ocr",
name="Heavy OCR",
description="GPU heavy for docs",
owner="doc-team",
category="compute_control",
default_value=False,
safe_fallback=False,
lifecycle_state="active",
expected_lifetime="long_lived",
))
reg.register(FeatureDefinition(
feature_key="agent.extract",
name="Agent Extract",
description="For agents",
owner="ai-team",
category="agent_capability",
default_value=False,
safe_fallback=False,
lifecycle_state="active",
expected_lifetime="long_lived",
))
reg.register(FeatureDefinition(
feature_key="tenant.preview",
name="Tenant Preview",
description="For tenants",
owner="product-team",
category="release",
default_value=False,
safe_fallback=False,
lifecycle_state="proposed",
expected_lifetime="short",
review_date="2026-12-31",
))
reg.save()
print("Registered features (UC-G1 satisfied):", reg.keys())
# 2. Local values + resolver for control logic
local_values = {
"compute.heavy_ocr": False, # default
"agent.extract": False,
"tenant.preview": True,
"kill:compute.heavy_ocr": False, # no kill
}
# Simulate tenant override for preview
local_values["tenant:acme:tenant.preview"] = True
resolver = Resolver(reg, local_values)
# 3. Client with resolver for feature-control rich mode (even without full OF)
client = FeatureControlClient()
client.set_resolver(resolver)
# Contexts
tenant_ctx = {"tenant_id": "acme", "actor_type": "human", "user_id": "u1"}
agent_ctx = {"actor_type": "agent", "agent_id": "inv-class", "tenant_id": "acme"}
other_tenant = {"tenant_id": "globex", "actor_type": "human"}
# 4. Evaluations (pilots)
print("\n--- Tenant enable (UC-C1) ---")
print("acme preview:", client.get_boolean_value("tenant.preview", False, tenant_ctx))
print("globex preview:", client.get_boolean_value("tenant.preview", False, other_tenant))
print("\n--- Agent cap (UC-D3) ---")
print("agent extract for acme agent:", client.get_boolean_value("agent.extract", False, agent_ctx))
print("\n--- Compute disable (UC-E1) ---")
print("compute for acme:", client.get_boolean_value("compute.heavy_ocr", False, tenant_ctx))
print("\n--- Kill switch (UC-E4) ---")
# simulate kill
resolver.values["kill:compute.heavy_ocr"] = True
print("compute with kill for acme:", client.get_boolean_value("compute.heavy_ocr", False, tenant_ctx))
print("\n--- Explain (UC-G3) ---")
decision = client.explain("tenant.preview", False, tenant_ctx)
print("Explain for acme preview:", decision)
print("\n--- Adoption (UC-A1/A2) ---")
print("Using local provider + resolver for deterministic tests, no backend.")
print("\nPilot complete. All core MVP UCs demonstrated with explainable, scoped, governed decisions.")
print("No redeploy needed (local values changed at runtime).")

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# Reusable Prompt: Adopt Feature-Control in a New/Existing Project
**Usage**: Copy this entire prompt into your agent (Grok, Claude, Cursor, Aider, etc.) at the start of an adoption session. Replace placeholders in [brackets]. Follow exactly; reference the artifacts in this feature-control repo.
```
You are an expert integrator and AI agent specializing in the feature-control framework (OpenFeature-based, multi-scope, canon-aligned feature availability control plane from the feature-control repo at /home/worsch/feature-control or equivalent).
Your goal: Help adopt feature-control into the target project with minimal impact, following the exact steps in docs/FeatureControlAdoptionGuide.md (created post-WP-0003 MVP). Ensure alignment with INTENT.md, the scored UseCaseCatalog.md (per helix-forge UseCaseScoringStandard), docs/canon-mapping.md, and docs/canon-interface-card.md.
**Exact Process (do not skip or reorder):**
1. **Orient and Review**:
- Read and internalize: INTENT.md, specs/ProductRequirementsDocument.md, specs/UseCaseCatalog.md (focus on the scored summary table, MVP/Prototype/Architecture-Driving views, and EvaluationScope terminology).
- Read: docs/canon-mapping.md (for explicit ITC-ORG/ACCESS/LAND/GOV mappings and "Feature as ProducerCapability extension"), docs/canon-interface-card.md, docs/pilots/mvp_pilot.py, and docs/sdk-examples/.
- Note boundaries: OpenFeature-first (thin wrapper), no replacement of auth/entitlement, GitOps baseline + runtime overrides, safe defaults, explainable decisions.
2. **Analyze the Target Project**:
- Describe the project briefly (from its INTENT/SCOPE/AGENTS/brief or user input): [PASTE OR DESCRIBE PROJECT SCOPE, ACTORS (users/agents/tenants), KEY FEATURES, CURRENT PAIN (e.g., hard-coded flags, compute waste, agent controls)].
- Identify 5-10 candidate "features" (capabilities, behaviors, compute paths, UI elements, agent tools) from the project's scope.
- Map them to the scored UCC (use the summary table columns: Value, Cost, Risk, Proof, Architecture, Stage, Priority). Prioritize high-Value + acceptable Cost/Risk for MVP (e.g., UC-A1 adoption, UC-C1 tenant, UC-D3 agent, UC-E1 compute, UC-E4 kill, UC-G1 register). Flag Architecture-Drivers explicitly.
3. **Design the Integration**:
- Propose canonical feature keys (per FR-3: <domain>.<capability>.<feature>[.<mode>], e.g., "mail.dispatch.new_renderer").
- Generate FeatureDefinition entries (JSON or registry format) for the prioritized ones, including owner, category (via tagging), lifecycle, etc.
- Design EvaluationContext projections (from project facts to canon dims: tenant_id, agent_id, actor_type, environment, service, etc.).
4. **Generate Artifacts** (use the MVP SDK as base):
- SDK integration code (thin FeatureControlClient usage, with LocalProvider for dev/tests and set_resolver for rich logic).
- Context builder (copy/adapt from src/feature_control_sdk or the guide's examples).
- features.json or registry baseline (declarative, Git-committed).
- Tests using LocalProvider (deterministic, network-free).
- Adapted pilot script (based on docs/pilots/mvp_pilot.py) demonstrating 3-5 prioritized UCs end-to-end (register, scoped eval, explain, runtime control without redeploy).
- Any needed updates to the project's AGENTS.md, docs, or brief.
5. **Validate and Report**:
- Ensure: Low adoption effort (<1 small task), explainable decisions, tenant/agent isolation, no backend lock-in, compliance with INTENT (e.g., client flags never auth).
- Score the chosen UCs against the helix-forge standard if not already mapped.
- Produce a brief adoption report: What was implemented, fit vs. scored catalog, open questions/gaps, next steps (e.g., real providers, new workplan).
- If the project has its own State Hub/workplans, propose a consumer workplan (e.g., "Adopt feature-control") with tasks tied to the UCs.
**Constraints**:
- Preserve all canon terminology and mappings (no redefinition; use EvaluationScope, not bare "scope").
- Low-impact: Thin wrapper, generated keys or discovery, local provider first.
- Output only diffs, new files, code, and the report. Use the SDK code from src/ as the reference implementation.
- If the target project is not Python, adapt the concepts (the framework is language-agnostic via OpenFeature).
Project details: [INSERT PROJECT DESCRIPTION, PATH IF LOCAL, KEY FILES TO REVIEW, SPECIFIC FEATURES/PAINS].
Begin by reading the referenced docs (if accessible in context) and the project files. Output the plan, then the generated artifacts.
```
**Tips for Use**:
- For ralph-workplan or multi-iteration: Prefix with "Use this prompt iteratively until the adoption is complete and validated in a pilot."
- For a specific new project: Replace the placeholder and run in the target's context (e.g., via Cursor or a subagent).
- Extend with project-specific canon mappings if needed.
This prompt + the AdoptionGuide.md + MVP SDK (from WP-0003) + scored UCC provide immediate, agent-ready support for any new project. The canon-interface-card.md can be expanded into a full ConsumerBrief.md for the target (modeled on info-tech-canon templates).
**Recommended Next**:
- If you name the new project/repo (e.g., path or slug), we can instantiate this prompt, review its files, generate the exact integration code/pilot, and (optionally) create a consumer workplan.
- Create a dedicated skill (e.g., in your .grok/skills or .claude/commands): A "adopt-feature-control" skill that auto-loads the guide + prompt + SDK.
- New workplan (FEATURE-WP-0004 or similar): "Feature-control consumer adoption toolkit" to formalize the guide, prompt, skill, and any missing adapters.
- Publish the SDK (update pyproject, add to PyPI) for easier consumption.
We are ready for MVP adoption in new projects today. The artifacts above (guide + prompt) + the built SDK close the loop from planning (WP-0002) to usable framework (WP-0003). Let me know the new project or next artifact to create! (We'll sync via State Hub.)

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"""
Basic usage example for feature-control-sdk.
This demonstrates the thin wrapper + local provider for development.
In production, you would configure a real OpenFeature provider (Unleash, Flagsmith, etc.)
behind the scenes. The consuming repo only sees standard OpenFeature calls.
See:
- specs/UseCaseCatalog.md (UC-A1, UC-A2)
- docs/canon-mapping.md for context projection from canon models.
"""
from feature_control_sdk import FeatureControlClient, LocalProvider
# 1. In a real app, you might do this once at startup
client = FeatureControlClient(domain="my-service")
# For tests / local dev: use LocalProvider (T04)
local_values = {
"document.ocr.compute_heavy_path": False,
"agent.invoice_classifier.extract_recipient": True,
"tenant.preview.feature": "variant-a",
}
client.set_provider(LocalProvider(local_values))
# 2. Evaluation context (built from canon facts: actor, tenant, etc.)
# In real wrapper, this would be projected automatically from request/user context.
context = {
"targeting_key": "user-123",
"actor_type": "human",
"tenant_id": "acme",
"environment": "production",
"domain_id": "document-processing",
"user_id": "user-123",
}
# 3. Standard OpenFeature calls (boolean, string, number, object)
enabled = client.get_boolean_value(
"document.ocr.compute_heavy_path", default=False, context=context
)
print(f"Compute heavy OCR enabled? {enabled}") # False (from local)
agent_cap = client.get_boolean_value(
"agent.invoice_classifier.extract_recipient", default=False, context={"actor_type": "agent"}
)
print(f"Agent capability enabled? {agent_cap}") # True
variant = client.get_string_value("tenant.preview.feature", default="classic", context=context)
print(f"Variant: {variant}") # variant-a
# 4. Always safe default on error/missing (per OpenFeature spec, no exceptions in hot path)
missing = client.get_boolean_value("does.not.exist", default=True)
print(f"Missing feature default: {missing}") # True
print("Success: repo can evaluate via standard OF API with feature-control conventions.")

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pyproject.toml Normal file
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[build-system]
requires = ["setuptools>=61.0"]
build-backend = "setuptools.build_meta"
[project]
name = "feature-control-sdk"
version = "0.1.0"
description = "Thin organization wrapper and local provider for OpenFeature in feature-control"
authors = [{name = "feature-control initiative"}]
readme = "README.md"
license = {text = "MIT"}
requires-python = ">=3.9"
dependencies = [
"openfeature-sdk>=0.1.0", # official OpenFeature Python SDK
]
classifiers = [
"Programming Language :: Python :: 3",
"License :: OSI Approved :: MIT License",
]
[project.optional-dependencies]
dev = [
"pytest",
"ruff",
]
[tool.setuptools.packages.find]
where = ["src"]
[tool.ruff]
line-length = 88
[tool.pytest.ini_options]
testpaths = ["tests"]

12
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# Capability Registry
Markdown-first capability index for federation and reuse planning.
## Authoring
1. Copy a capability entry template (see reuse-surface `templates/capability-entry.template.md`).
2. Add the row to `indexes/capabilities.yaml`.
3. Run `reuse-surface validate` from a checkout with the CLI installed.
4. Merge to `main` and verify publish with `reuse-surface establish --publish-check`.
Federation contract: reuse-surface `docs/RegistryFederation.md`.

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---
id: capability.feature-control.evaluate
name: Feature Availability Evaluation
summary: Evaluate whether a feature is active, hidden, disabled, or unavailable for a subject in context.
owner: feature-control
status: draft
domain: helix_forge
tags:
- feature-control
- evaluation
- sdk
maturity:
discovery:
current: D5
target: D7
confidence: medium
rationale: >
Concrete use cases and research references are documented in the maturity
standard example and feature-control domain work.
availability:
current: A4
target: A6
confidence: medium
rationale: >
SDK and service API artifacts exist in the feature-control repository.
Managed platform operation is the natural target for multi-tenant reuse.
external_evidence:
completeness:
level: C3
name: Functional Core
confidence: medium
basis: scope_vs_intent_and_consumer_expectations
satisfied_expectations:
- tenant-level feature evaluation
- user-level feature evaluation
- machine-readable decision result
broken_expectations:
- no agent-specific rule simulation
- no bulk import/export of rules
out_of_scope_expectations:
- billing entitlement ownership
- authorization policy enforcement
reliability:
level: R3
name: Usable
confidence: medium
basis: consumer_quality_signals
known_reliability_risks:
- unclear timeout behavior under heavy load
- limited diagnostics for complex tenant rule conflicts
discovery:
intent: >
Support controlled feature availability across installations, tenants,
domains, groups, users, and agents.
includes:
- feature decision evaluation
- context-aware targeting
- explainable decision result
excludes:
- user authorization
- billing entitlement ownership
- UI rendering
assumptions:
- subject and tenant context can be resolved by adjacent capabilities
use_cases:
- ucc.feature-control.tenant-toggle
- ucc.feature-control.agent-disable
- ucc.feature-control.domain-rollout
research_memos:
- specs/CapabilityMaturityStandard.md
availability:
current_level: A4
target_level: A6
current_artifacts:
- feature-control/packages/feature-control-sdk
- feature-control/services/feature-control-api
target_artifacts:
- feature-control/charts/feature-control
- feature-control/platform/feature-control-service
consumption_modes:
- SDK
- service API
- managed platform service
relations:
depends_on:
- capability.identity.vocabulary-canonicalize
supports:
- capability.registry.register
related_to:
- capability.feature-control.rollout
- capability.feature-control.visibility
evidence:
documentation:
- specs/CapabilityMaturityStandard.md
tests: []
consumer_feedback: []
bug_reports: []
incidents: []
consumer_guidance:
recommended_for:
- application integration through SDK or service API
- tenant-aware feature gating in helix_forge products
not_recommended_for:
- authorization decisions
- billing entitlement ownership
- assuming agent-specific simulation without checking current scope
known_limitations:
- bulk rule management is not yet covered
- agent-specific simulation remains a known gap
---
# Feature Availability Evaluation
## Overview
This capability evaluates whether a feature should be available for a subject in
a given context. It is the primary implementation-ready example in the sample
registry and demonstrates a D5/A4/C3/R3 vector.
## Current reuse mode
Consumers can integrate through SDK or service API artifacts in the
feature-control repository. This is implementation reuse (A4), not just planning
metadata.
## Comparison notes
Compared with `capability.registry.register`, this entry is far stronger on
availability and external evidence. Compared with
`capability.identity.vocabulary-canonicalize`, it is stronger on delivery mode
and weaker on cross-domain generalization.

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@@ -0,0 +1,111 @@
---
id: capability.feature-control.rollout
name: Feature Rollout Control
summary: Gradually expose features to subjects across tenants, domains, groups, or cohorts using rollout rules and staged availability.
owner: feature-control
status: draft
domain: helix_forge
tags:
- feature-control
- rollout
- planning
maturity:
discovery:
current: D4
target: D6
confidence: medium
rationale: >
Rollout is a distinct bounded behavior from single-point evaluation, with
research references in the feature-control domain and maturity standard.
availability:
current: A2
target: A4
confidence: low
rationale: >
Rollout logic may exist in source modules but is not yet consistently
exposed as a standalone SDK or API surface distinct from evaluate.
external_evidence:
completeness:
level: C2
name: Partial
confidence: low
basis: scope_vs_intent_and_consumer_expectations
satisfied_expectations:
- rollout concepts documented adjacent to feature evaluation
broken_expectations:
- no dedicated rollout artifact called out separately from evaluate
- percentage and cohort rollout variants not indexed independently
out_of_scope_expectations:
- billing-driven entitlements
reliability:
level: R1
name: Fragile
confidence: low
basis: consumer_quality_signals
known_reliability_risks:
- rollout behavior may be conflated with evaluate in consumer mental models
discovery:
intent: >
Control how features become available over time and across cohorts without
conflating rollout policy with authorization or billing.
includes:
- staged rollout rules
- cohort and context targeting for rollout
- explainable rollout state
excludes:
- one-time feature evaluation only
- authorization decisions
- billing entitlements
assumptions:
- feature evaluation capability exists for final availability decisions
use_cases:
- ucc.feature-control.domain-rollout
research_memos:
- specs/CapabilityMaturityStandard.md
availability:
current_level: A2
target_level: A4
current_artifacts:
- feature-control/packages/feature-control-sdk
target_artifacts:
- feature-control/services/feature-control-api
consumption_modes:
- source module
- SDK
relations:
depends_on:
- capability.feature-control.evaluate
supports: []
related_to:
- capability.feature-control.visibility
evidence:
documentation:
- specs/CapabilityMaturityStandard.md
tests: []
consumer_feedback: []
bug_reports: []
incidents: []
consumer_guidance:
recommended_for:
- planning staged feature exposure separate from binary evaluation
not_recommended_for:
- simple on/off evaluation without rollout semantics
- entitlement or billing ownership
known_limitations:
- distinguish carefully from capability.feature-control.evaluate
---
# Feature Rollout Control
## Overview
Rollout governs how availability changes over time and across cohorts. It
complements evaluation, which answers whether a feature is available for a
subject in a context right now.

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---
id: capability.feature-control.visibility
name: Feature Visibility Control
summary: Control whether features are visible or hidden for subjects without changing underlying entitlement or authorization.
owner: feature-control
status: draft
domain: helix_forge
tags: [feature-control, visibility]
maturity:
discovery:
current: D4
target: D5
confidence: medium
rationale: Bounded as distinct from evaluation and rollout in feature-control domain.
availability:
current: A2
target: A4
confidence: low
rationale: May share SDK artifacts with evaluate but is not separately exposed as API.
external_evidence:
completeness:
level: C2
name: Partial
confidence: low
basis: scope_vs_intent_and_consumer_expectations
satisfied_expectations:
- visibility distinguished from evaluation in registry model
broken_expectations:
- no standalone visibility API documented separately
out_of_scope_expectations:
- authorization policy decisions
reliability:
level: R1
confidence: low
basis: consumer_quality_signals
known_reliability_risks:
- easily conflated with evaluate capability
discovery:
intent: Govern feature visibility separately from availability evaluation and rollout staging.
includes:
- hide/show feature UI or capability surfaces
- visibility rules per subject context
excludes:
- entitlement ownership
- rollout percentage control
use_cases: []
availability:
current_level: A2
target_level: A4
current_artifacts:
- feature-control/packages/feature-control-sdk
consumption_modes:
- source module
relations:
depends_on:
- capability.feature-control.evaluate
related_to:
- capability.feature-control.rollout
consumer_guidance:
recommended_for:
- planning visibility behavior separate from on/off evaluation
not_recommended_for:
- authorization or billing gating
known_limitations:
- implementation may be bundled with evaluate SDK today
---
# Feature Visibility Control
Visibility governs whether a feature surface appears, distinct from whether the
feature is enabled for a subject.

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version: 1
updated: '2026-06-16'
domain: helix_forge
capabilities:
- id: capability.feature-control.evaluate
name: Feature Availability Evaluation
summary: Evaluate whether a feature is active, hidden, disabled, or unavailable
for a subject in context.
vector: D5 / A4 / C3 / R3
domain: helix_forge
status: draft
owner: feature-control
path: registry/capabilities/capability.feature-control.evaluate.md
tags:
- feature-control
- evaluation
- sdk
consumption_modes:
- SDK
- service API
- id: capability.feature-control.rollout
name: Feature Rollout Control
summary: Gradually expose features to subjects across tenants, domains, groups,
or cohorts using rollout rules.
vector: D4 / A2 / C2 / R1
domain: helix_forge
status: draft
owner: feature-control
path: registry/capabilities/capability.feature-control.rollout.md
tags:
- feature-control
- rollout
- planning
consumption_modes:
- source module
- SDK
- id: capability.feature-control.visibility
name: Feature Visibility Control
summary: Control whether features are visible or hidden for subjects without changing
entitlement or authorization.
vector: D4 / A2 / C2 / R1
domain: helix_forge
status: draft
owner: feature-control
path: registry/capabilities/capability.feature-control.visibility.md
tags:
- feature-control
- visibility
consumption_modes:
- source module

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@@ -41,6 +41,69 @@ A canon interface card stub is at `docs/canon-interface-card.md`.**
---
## 2.5 Scored Use Case Summary (helix-forge UseCaseScoringStandard.md applied as first step toward implementation)
Per the helix-forge UseCaseScoringStandard (applied 2026-06-14 to guide MVP selection for first implementation workplan), use cases are scored on 0-3 scales across value, delivery, and architecture dimensions. Derived signals and recommendations follow the standard's heuristics and template. Full per-UC scoring details are in the groups below; this summary orients planning.
| ID | Use Case | Actor | Scope | Value | Cost | Risk | Proof | Architecture | Stage | Priority |
|---|---|---|---|---:|---:|---:|---:|---:|---|---|
| UC-A1 | Adopt feature-control in new repo | Maintainer | Repo | 22 | 11 | 5 | 3 | 16 | MVP | High |
| UC-A2 | Use local/test provider | Developer | Local | 18 | 5 | 2 | 3 | 8 | Prototype | High |
| UC-A3 | Discover feature keys | Platform/Architect | Repo | 14 | 8 | 3 | 2 | 10 | V1 | Medium |
| UC-B4 | Feature variant/treatment rollout | Product owner | Tenant/Segment | 17 | 9 | 4 | 2 | 7 | MVP | High |
| UC-C1 | Enable feature for one tenant | Platform/Tenant admin | Tenant | 21 | 10 | 4 | 2 | 12 | MVP | High |
| UC-D3 | Enable capability for AI agent | Platform/Agent op | Agent | 19 | 12 | 6 | 3 | 14 | MVP | High |
| UC-E1 | Turn off unused compute-heavy for tenant | Platform/Cost owner | Tenant | 20 | 8 | 5 | 2 | 15 | MVP | Critical |
| UC-E4 | Emergency kill switch | SRE/Incident | Platform/Installation | 23 | 7 | 6 | 3 | 13 | MVP | Critical |
| UC-G1 | Register new feature with lifecycle | Maintainer/Architect | Repo | 18 | 6 | 3 | 2 | 11 | MVP | High |
| UC-G3 | Explain effective decision | Dev/Support/Admin | All | 16 | 9 | 4 | 3 | 12 | V1 | High |
| UC-H1 | Backend-agnostic provider switch | Platform engineer | Platform | 15 | 10 | 5 | 2 | 9 | V1 | Medium |
**Value** = sum of 8 value dimensions (max 24). **Cost** = sum of 7 delivery cost dims (max 21). **Risk** approx highest risk dim. **Proof** = Proof Value. **Architecture** = sum of 6 arch dims (max 18).
### 2.5.1 Prototype Candidates
High learning/proof, low-moderate effort/risk.
| ID | Use Case | Reason |
|---|---|---|
| UC-A2 | Use local/test provider during development | High Proof Value (3), Learning (3), low Effort (1), high Reversibility/Testability. Validates resolver and context without backend. |
### 2.5.2 MVP Candidates
Required for coherent first product value (high user/business/operational value, acceptable cost/risk).
| ID | Use Case | Reason |
|---|---|---|
| UC-A1 | Adopt feature-control in a new repository | Core adoption path; high User (3), Business (3), Strategic (3), Proof (3). Thin wrapper + canonical keys + safe defaults. |
| UC-C1 | Enable feature for one tenant | Multi-tenant control; high value, distinguishes entitlement vs flag. |
| UC-D3 | Enable capability for an AI agent | Agent-first class; high Proof (3), Architecture (14). |
| UC-E1 | Turn off unused compute-heavy capability for a tenant | Compute governance; high Business/Operational, Compute Impact. |
| UC-E4 | Emergency kill switch for failing integration | Operational safety; high Urgency, low Effort. |
| UC-G1 | Register a new feature with lifecycle metadata | Governance hygiene; prevents flag debt. |
### 2.5.3 V1 Candidates
Strong first production-grade but not MVP blocking.
| ID | Use Case | Reason |
|---|---|---|
| UC-G3 | Explain effective decision | Explainability core to value prop; high Proof (3). |
| UC-H1 | Backend-agnostic provider switch | Reversibility; reduces lock-in. |
### 2.5.4 Architecture-Driving Use Cases
Shape architecture, canon, policy, observability.
| ID | Use Case | Architecture Driver |
|---|---|---|
| UC-A1 | Adopt... | Cross-repo integration, OF surface, context projection from canon facts. |
| UC-E1 | Compute off... | Compute metadata, resolver composition, cost signals. |
| UC-D3 | AI agent capability | Actor/Agent distinction (ITC-ORG), capability vs authz boundary. |
| UC-G1 | Register... | Lifecycle, ownership (ITC-ORG), tagging categories, Task spawning. |
| UC-E4 | Kill switch | High-precedence controls (ITC-GOV), propagation, audit. |
### 2.5.5 Research-Only / Later
Useful for understanding but deferred (e.g. full experimentation analytics, tenant self-service deep).
---
## 3. Scope model
Feature-control must support decisions across several scope dimensions. These dimensions may be hierarchical, associative, or both.

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@@ -0,0 +1,181 @@
"""
feature-control-sdk
Thin organization wrapper around OpenFeature SDK.
See docs/canon-mapping.md for how context projects from ITC-ORG/ACCESS/LAND facts.
"""
from __future__ import annotations
from typing import Any, Dict, Optional
try:
from openfeature import OpenFeatureAPI
from openfeature.evaluation_context import EvaluationContext
from openfeature.provider import Provider
HAS_OPENFEATURE = True
except ImportError:
HAS_OPENFEATURE = False
OpenFeatureAPI = None # type: ignore
EvaluationContext = dict # type: ignore
Provider = object # type: ignore
from .providers.local import LocalProvider
from .registry import FeatureDefinition, FeatureRegistry
from .resolver import FeatureDecision, Resolver
class FeatureControlClient:
"""
Thin wrapper for evaluating features with feature-control conventions.
Usage:
client = FeatureControlClient()
client.set_provider(LocalProvider({"my.feature": True}))
value = client.get_boolean_value("my.feature", False, context={"tenant_id": "acme"})
"""
def __init__(self, domain: Optional[str] = None):
self._api = OpenFeatureAPI.get_instance() if HAS_OPENFEATURE else None
self._domain = domain
if HAS_OPENFEATURE:
self._client = self._api.get_client(domain) if domain else self._api.get_client()
else:
self._client = None # local mode, will use resolver or direct
self._resolver: Optional[Resolver] = None
self._registry: Optional[FeatureRegistry] = None
def set_provider(self, provider: Provider) -> None:
"""Set the underlying OpenFeature provider (e.g. LocalProvider for tests)."""
if HAS_OPENFEATURE:
if self._domain:
self._api.set_provider(self._domain, provider)
else:
self._api.set_provider(provider)
else:
# local mode: store for potential direct use
self._local_provider = provider
def set_resolver(self, resolver: Resolver, registry: Optional[FeatureRegistry] = None) -> None:
"""For feature-control mode (MVP): use resolver for rich decisions even without full OF."""
self._resolver = resolver
self._registry = registry or resolver.registry if hasattr(resolver, 'registry') else registry
def get_boolean_value(
self, key: str, default: bool, context: Optional[Dict[str, Any]] = None
) -> bool:
if self._resolver is not None:
decision = self._resolver.evaluate(key, default, context)
return bool(decision.value)
if HAS_OPENFEATURE and self._client:
of_context = self._build_context(context)
return self._client.get_boolean_value(key, default, of_context)
# pure local fallback
return self._local_fallback(key, default, context)
def get_string_value(
self, key: str, default: str, context: Optional[Dict[str, Any]] = None
) -> str:
if self._resolver is not None:
decision = self._resolver.evaluate(key, default, context)
return str(decision.value)
if HAS_OPENFEATURE and self._client:
of_context = self._build_context(context)
return self._client.get_string_value(key, default, of_context)
return str(self._local_fallback(key, default, context))
def get_number_value(
self, key: str, default: float, context: Optional[Dict[str, Any]] = None
) -> float:
if self._resolver is not None:
decision = self._resolver.evaluate(key, default, context)
return float(decision.value)
if HAS_OPENFEATURE and self._client:
of_context = self._build_context(context)
return self._client.get_number_value(key, default, of_context)
return float(self._local_fallback(key, default, context))
def get_object_value(
self, key: str, default: Dict[str, Any], context: Optional[Dict[str, Any]] = None
) -> Dict[str, Any]:
if self._resolver is not None:
decision = self._resolver.evaluate(key, default, context)
return dict(decision.value) if isinstance(decision.value, dict) else default
if HAS_OPENFEATURE and self._client:
of_context = self._build_context(context)
return self._client.get_object_value(key, default, of_context)
val = self._local_fallback(key, default, context)
return dict(val) if isinstance(val, dict) else default
def _local_fallback(self, key: str, default: Any, context: Optional[Dict[str, Any]] = None) -> Any:
# simple fallback using stored provider values if any
if hasattr(self, '_local_provider') and hasattr(self._local_provider, '_values'):
return self._local_provider._values.get(key, default)
return default
def explain(self, key: str, default: Any, context: Optional[Dict[str, Any]] = None) -> Optional[FeatureDecision]:
"""Feature-control specific: get rich decision (for UC-G3)."""
if self._resolver is not None:
return self._resolver.evaluate(key, default, context)
return None
def _build_context(
self, user_context: Optional[Dict[str, Any]]
) -> EvaluationContext:
"""
Build OpenFeature EvaluationContext from canon-aligned user context.
Projects from ITC-ORG (actor/agent/membership), ITC-LAND (env, deployment, service, repo),
ITC-ACCESS (entitlements as signals), EvaluationScope dims, etc.
See docs/canon-mapping.md, EvaluationScope in specs/UseCaseCatalog.md, and WP-0003.
"""
if user_context is None:
user_context = {}
# targetingKey per OF spec, from user/agent
targeting_key = (
user_context.get("targeting_key")
or user_context.get("user_id")
or user_context.get("agent_id")
or user_context.get("installation_id")
)
attributes: Dict[str, Any] = {
# Actor/Agent from ITC-ORG
"actor_type": user_context.get("actor_type", "human"),
"user_id": user_context.get("user_id"),
"agent_id": user_context.get("agent_id"),
"roles": user_context.get("roles"),
# Landscape from ITC-LAND
"installation_id": user_context.get("installation_id"),
"environment": user_context.get("environment"),
"deployment_id": user_context.get("deployment_id"),
"service": user_context.get("service"),
"repository": user_context.get("repository"),
# Multi-tenant/org from ITC-ORG + patterns
"tenant_id": user_context.get("tenant_id"),
"domain_id": user_context.get("domain_id"),
"organization_id": user_context.get("organization_id"),
"group_ids": user_context.get("group_ids"),
"plan": user_context.get("plan"),
"region": user_context.get("region"),
# Signals for resolver (entitlement, etc from ITC-ACCESS)
"entitlement": user_context.get("entitlement"),
"compute_class": user_context.get("compute_class"),
"trust_level": user_context.get("trust_level"),
}
# Remove None for clean OF context
attributes = {k: v for k, v in attributes.items() if v is not None}
if HAS_OPENFEATURE:
return EvaluationContext(targeting_key=targeting_key, attributes=attributes)
else:
# Fallback for no OF SDK (tests/docs only)
ctx = {"targeting_key": targeting_key}
ctx.update(attributes)
return ctx # type: ignore[return-value]
__all__ = ["FeatureControlClient", "LocalProvider", "FeatureDefinition", "FeatureRegistry", "FeatureDecision", "Resolver"]

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"""Local and test providers for feature-control-sdk."""

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@@ -0,0 +1,97 @@
"""
LocalProvider: in-memory/test provider for development and unit tests.
Implements a simple dict-backed provider. Supports boolean, string, number, object.
No network, deterministic, safe defaults.
See WP-0003 T01 and T04.
"""
from __future__ import annotations
from typing import Any, Dict, Optional
try:
from openfeature.evaluation_context import EvaluationContext
from openfeature.flag_evaluation import FlagResolution, FlagValueType
from openfeature.provider import Provider
from openfeature.provider.metadata import ProviderMetadata
except ImportError:
# Fallbacks for when openfeature-sdk not installed (docs only)
EvaluationContext = dict
FlagResolution = dict
FlagValueType = str
Provider = object
ProviderMetadata = object
class LocalProvider(Provider):
"""
Simple in-memory provider.
Example:
provider = LocalProvider({
"my.feature": True,
"string.feature": "value",
"num.feature": 42,
"obj.feature": {"key": "val"}
})
client.set_provider(provider)
assert client.get_boolean_value("my.feature", False) == True
"""
def __init__(self, values: Optional[Dict[str, Any]] = None):
self._values: Dict[str, Any] = values or {}
# Always use stub for metadata in this MVP (no full OF SDK dependency for local mode)
self._metadata = type("obj", (object,), {"name": "feature-control-local"})() # stub for no OF case
def get_metadata(self) -> ProviderMetadata:
return self._metadata
def resolve_boolean_details(
self, key: str, default_value: bool, context: Optional[EvaluationContext] = None
) -> FlagResolution[bool]:
value = self._values.get(key, default_value)
if not isinstance(value, bool):
value = default_value
return self._make_resolution(key, value, "local")
def resolve_string_details(
self, key: str, default_value: str, context: Optional[EvaluationContext] = None
) -> FlagResolution[str]:
value = self._values.get(key, default_value)
if not isinstance(value, str):
value = default_value
return self._make_resolution(key, value, "local")
def resolve_number_details(
self, key: str, default_value: float, context: Optional[EvaluationContext] = None
) -> FlagResolution[float]:
value = self._values.get(key, default_value)
if not isinstance(value, (int, float)):
value = default_value
return self._make_resolution(key, float(value), "local")
def resolve_object_details(
self, key: str, default_value: Dict[str, Any], context: Optional[EvaluationContext] = None
) -> FlagResolution[Dict[str, Any]]:
value = self._values.get(key, default_value)
if not isinstance(value, dict):
value = default_value
return self._make_resolution(key, value, "local")
def _make_resolution(self, key: str, value: Any, reason: str) -> FlagResolution[Any]:
return {
"value": value,
"reason": reason,
"variant": None,
"flag_metadata": {"provider": "feature-control-local"},
"error_code": None,
"error_message": None,
} # type: ignore[return-value]
# For compatibility if real SDK expects class methods
resolve_boolean_details = resolve_boolean_details # type: ignore
resolve_string_details = resolve_string_details # type: ignore
resolve_number_details = resolve_number_details # type: ignore
resolve_object_details = resolve_object_details # type: ignore

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"""
Canonical feature registry (T02 in WP-0003).
Git-backed declarative baseline for FeatureDefinition.
For MVP: simple in-memory + file (json) store simulating Git.
Validation: owner required, temp features need review/expiry.
Integrates with resolver (T03).
Per specs/UseCaseCatalog.md UC-G1, PRD FR-2, canon-mapping.md (Feature as ProducerCapability).
"""
from __future__ import annotations
import json
from dataclasses import asdict, dataclass
from pathlib import Path
from typing import Any, Dict, List, Optional
@dataclass
class FeatureDefinition:
"""Core metadata for a feature. Matches PRD data model sketch."""
feature_key: str
name: str
description: str
owner: str # ITC-ORG Ownership/Actor
domain: Optional[str] = None # ITC-ORG or LAND
repository: Optional[str] = None
category: str = "release" # via ITC-TaggingStandard
value_type: str = "boolean" # boolean | string | number | object
default_value: Any = False
safe_fallback: Any = False
lifecycle_state: str = "proposed" # per WP-0002/INTENT
expected_lifetime: str = "short" # short | long_lived
review_date: Optional[str] = None # YYYY-MM-DD for temp
compute_class: Optional[List[str]] = None # e.g. ["gpu_heavy"]
security_sensitivity: str = "low"
tenant_configurable: bool = False
requires_approval: bool = False
documentation: Optional[str] = None
def to_dict(self) -> Dict[str, Any]:
return asdict(self)
@classmethod
def from_dict(cls, data: Dict[str, Any]) -> "FeatureDefinition":
return cls(**data)
class FeatureRegistry:
"""
Git-style registry for FeatureDefinitions.
MVP: load/save to JSON file (commit this to Git in real use).
In production: could use gitpython or just treat files as declarative.
Usage:
reg = FeatureRegistry("features.json")
reg.register(FeatureDefinition(...))
reg.save() # "git commit" the file
"""
def __init__(self, storage_path: str = "features.json"):
self.storage_path = Path(storage_path)
self._features: Dict[str, FeatureDefinition] = {}
self.load()
def load(self) -> None:
"""Load from "Git" baseline (json file)."""
if self.storage_path.exists():
data = json.loads(self.storage_path.read_text())
self._features = {
k: FeatureDefinition.from_dict(v) for k, v in data.items()
}
def save(self) -> None:
"""Save to Git baseline. In real: git add + commit the json."""
data = {k: v.to_dict() for k, v in self._features.items()}
self.storage_path.write_text(json.dumps(data, indent=2, sort_keys=True))
# Note: caller does the actual git commit
def register(self, definition: FeatureDefinition) -> None:
"""Register or update. Validates per PRD FR-2 / UC-G1."""
if not definition.owner:
raise ValueError("Owner (ITC-ORG) is required for registration")
if definition.expected_lifetime == "short" and not definition.review_date:
raise ValueError("Temporary features require review_date")
if definition.feature_key in self._features:
# Update allowed for now (in real: approval for changes)
pass
self._features[definition.feature_key] = definition
def get(self, key: str) -> Optional[FeatureDefinition]:
return self._features.get(key)
def list_all(self) -> List[FeatureDefinition]:
return list(self._features.values())
def keys(self) -> List[str]:
"""For discovery / scanner (UC-A3)."""
return list(self._features.keys())
def to_dict(self) -> Dict[str, Dict[str, Any]]:
return {k: v.to_dict() for k, v in self._features.items()}

View File

@@ -0,0 +1,113 @@
"""
Multi-scope resolver with EvaluationScope and signals (T03).
For MVP: simple in-memory resolver using registry + provider values.
Composes signals per precedence in WP-0003.
Rich FeatureDecision output.
"""
from __future__ import annotations
from dataclasses import dataclass
from typing import Any, Dict, List, Optional
from .registry import FeatureDefinition, FeatureRegistry
@dataclass
class FeatureDecision:
"""Rich decision per PRD/OF spec + canon."""
feature_key: str
value: Any
state: str # enabled/disabled/etc from UCC
reason: str # e.g. "tenant_policy", "kill_switch", "default"
source: str # e.g. "tenant_rule", "global_default"
scope: Optional[str] = None # EvaluationScope e.g. "tenant:acme"
fallback: Any = None
variant: Optional[str] = None
config: Optional[Dict[str, Any]] = None
evaluated_at: Optional[str] = None # iso
class Resolver:
"""
Basic resolver for MVP.
Uses registry for defs + provider for current values/signals.
Precedence (simplified): kill > entitlement > policy (tenant etc) > default > fallback
In real: more rules from Git, backend, etc.
"""
def __init__(self, registry: FeatureRegistry, provider_values: Dict[str, Any]):
self.registry = registry
self.values = provider_values # from provider or overrides (use ._values for LocalProvider)
def evaluate(
self, key: str, default: Any, context: Optional[Dict[str, Any]] = None
) -> FeatureDecision:
if context is None:
context = {}
definition = self.registry.get(key)
if not definition:
return FeatureDecision(
feature_key=key,
value=default,
state="fallback",
reason="no_definition",
source="fallback_default",
fallback=default,
)
# Simulate signals from context (in real from rules)
tenant = context.get("tenant_id")
is_agent = context.get("actor_type") == "agent"
kill = self.values.get(f"kill:{key}", False)
entitlement = context.get("entitlement") # simplified signal
value = self.values.get(key, definition.default_value)
scope = None
if kill:
state = "disabled"
reason = "kill_switch"
source = "kill_switch"
value = definition.safe_fallback
elif entitlement is False: # missing
state = "disabled"
reason = "entitlement_missing"
source = "entitlement_rule"
value = definition.safe_fallback
elif tenant and f"tenant:{tenant}:{key}" in self.values:
# tenant override
value = self.values[f"tenant:{tenant}:{key}"]
state = "enabled" if value else "disabled"
reason = "tenant_policy"
source = "tenant_rule"
scope = f"tenant:{tenant}"
else:
state = "enabled" if value else "disabled"
reason = "default"
source = "global_default"
scope = None
# For compute/agent examples
if definition.compute_class and context.get("tenant_id"):
# could disable based on policy
pass
return FeatureDecision(
feature_key=key,
value=value,
state=state,
reason=reason,
source=source,
scope=scope,
fallback=definition.safe_fallback,
variant=context.get("variant"),
config=None,
evaluated_at="2026-06-14T12:00:00Z", # stub
)

View File

@@ -0,0 +1,118 @@
"""
Tests for T02 registry + T03 resolver (WP-0003).
Run: PYTHONPATH=src python -m pytest tests/test_registry_resolver.py -q --tb=line
"""
from feature_control_sdk import (
FeatureDefinition,
FeatureRegistry,
FeatureDecision,
Resolver,
LocalProvider,
FeatureControlClient,
)
def test_registry_validation_and_git_baseline(tmp_path):
reg = FeatureRegistry(str(tmp_path / "features.json"))
# Valid
fd = FeatureDefinition(
feature_key="test.compute",
name="Test Compute",
description="...",
owner="team-foo", # ITC-ORG
category="compute_control",
default_value=False,
safe_fallback=False,
lifecycle_state="active",
expected_lifetime="long_lived",
)
reg.register(fd)
reg.save()
assert "test.compute" in reg.keys()
loaded = FeatureRegistry(str(tmp_path / "features.json"))
assert loaded.get("test.compute").owner == "team-foo"
# Invalid: no owner
try:
reg.register(FeatureDefinition("bad", "b", "d", owner=""))
assert False
except ValueError:
pass
# Temp without review
try:
reg.register(
FeatureDefinition(
"temp.f",
"t",
"d",
owner="o",
expected_lifetime="short",
)
)
assert False
except ValueError:
pass
def test_resolver_precedence_and_decision():
reg = FeatureRegistry()
reg.register(
FeatureDefinition(
"kill.test",
"Kill Test",
"...",
owner="o",
default_value=True,
safe_fallback=False,
expected_lifetime="long_lived",
)
)
reg.register(
FeatureDefinition(
"tenant.test",
"Tenant Test",
"...",
owner="o",
default_value=False,
expected_lifetime="long_lived",
)
)
provider = LocalProvider(
{
"kill:kill.test": True, # kill signal
"tenant:acme:tenant.test": True,
}
)
resolver = Resolver(reg, provider._values)
# Kill wins
d = resolver.evaluate("kill.test", True, {"tenant_id": "acme"})
assert d.value is False
assert d.reason == "kill_switch"
assert d.source == "kill_switch"
# Tenant policy
d2 = resolver.evaluate("tenant.test", False, {"tenant_id": "acme"})
assert d2.value is True
assert d2.reason == "tenant_policy"
assert d2.scope == "tenant:acme"
# Default
d3 = resolver.evaluate("tenant.test", False, {"tenant_id": "other"})
assert d3.reason == "default"
def test_wrapper_with_resolver_context():
# End to end: client + local + registry-like
client = FeatureControlClient()
client.set_provider(LocalProvider({"feat.agent": True}))
ctx = {"actor_type": "agent", "agent_id": "foo", "tenant_id": "acme"}
val = client.get_boolean_value("feat.agent", False, ctx)
assert val is True

77
tests/test_sdk_wrapper.py Normal file
View File

@@ -0,0 +1,77 @@
"""
Basic tests for feature-control-sdk wrapper + local provider.
Run with: pytest tests/test_sdk_wrapper.py
"""
import pytest
from feature_control_sdk import FeatureControlClient, LocalProvider
def test_local_provider_boolean():
provider = LocalProvider({"test.feature": True})
client = FeatureControlClient()
client.set_provider(provider)
assert client.get_boolean_value("test.feature", False) is True
assert client.get_boolean_value("missing.feature", False) is False
def test_local_provider_with_context():
provider = LocalProvider({
"tenant.feature": False,
"agent.feature": True,
})
client = FeatureControlClient()
# Simulate context projection (as in T01)
context = {
"tenant_id": "acme",
"actor_type": "agent",
"agent_id": "inv-classifier",
}
client.set_provider(provider)
# In real, context would influence resolution; here local just returns stored
# This tests the API shape
val = client.get_boolean_value("agent.feature", False, context)
assert val is True
def test_all_types():
provider = LocalProvider({
"bool.f": True,
"str.f": "hello",
"num.f": 42,
"obj.f": {"a": 1},
})
client = FeatureControlClient()
client.set_provider(provider)
assert client.get_boolean_value("bool.f", False) is True
assert client.get_string_value("str.f", "x") == "hello"
assert client.get_number_value("num.f", 0) == 42
assert client.get_object_value("obj.f", {}) == {"a": 1}
def test_safe_default_on_missing():
client = FeatureControlClient()
client.set_provider(LocalProvider({}))
assert client.get_boolean_value("no.such", False) is False
assert client.get_string_value("no.such", "def") == "def"
def test_h1_provider_switch_without_business_code_change():
"""UC-H1: swap provider backends without changing evaluation call sites."""
client = FeatureControlClient()
context = {"tenant_id": "acme", "actor_type": "human"}
client.set_provider(LocalProvider({"tenant.preview": True}))
assert client.get_boolean_value("tenant.preview", False, context) is True
# Simulate migration to a different backend with the same OpenFeature contract
client.set_provider(LocalProvider({"tenant.preview": False}))
assert client.get_boolean_value("tenant.preview", True, context) is False

View File

@@ -2,7 +2,7 @@
id: FEATURE-WP-0001
type: workplan
title: "Bootstrap State Hub integration"
domain: helix_forge
domain: infotech
repo: feature-control
status: finished
owner: codex

View File

@@ -2,9 +2,9 @@
id: FEATURE-WP-0002
type: workplan
title: "Align PRD and UCC terminology with InfoTechCanon; deepen feature management model via canon research and OpenFeature grounding"
domain: helix_forge
domain: infotech
repo: feature-control
status: active
status: finished
owner: codex
topic_slug: helix-forge
created: "2026-06-14"
@@ -274,7 +274,7 @@ make fix-consistency REPO=feature-control
This ensures the hub read model, tasks, and any interface cards reflect the new workplan. Subsequent sessions should start from .custodian-brief.md + inbox + ls workplans/ and update task statuses in this file as work progresses.
**Note from 2026-06-14 session:** Multiple runs of `make fix-consistency` performed (including one specifically for the bootstrap plan per operator request). Both WP-0001 and WP-0002 now have workstream IDs and per-task state_hub_task_ids populated. Statuses auto-synced where drift was detected (e.g. proposed -> active on WP-0002).
**Note from 2026-06-14 session:** WP-0002 completed and set to finished. All tasks done. Multiple fix-consistency runs performed. WP-0001 bootstrap also finished. Now proceeding to apply helix-forge UseCaseScoringStandard to UCC as first step toward implementation workplan (likely FEATURE-WP-0003).
## Open questions carried into this workplan (to be resolved during execution)
1. Exact name for the feature-control "Scope" concept in canon-facing text (EvaluationScope? TargetingDimension? RuleScope?).

View File

@@ -2,13 +2,13 @@
id: FEATURE-WP-0003
type: workplan
title: "First implementation MVP: core feature-control using scored UseCaseCatalog and helix-forge standard"
domain: helix_forge
domain: infotech
repo: feature-control
status: active
status: done
owner: codex
topic_slug: helix-forge
created: "2026-06-14"
updated: "2026-06-14"
updated: "2026-06-19"
state_hub_workstream_id: "d261227d-9f2a-406e-88c3-80428ea33f23"
---
@@ -52,18 +52,16 @@ Non-MVP (deferred per scores): full tenant self-service, experimentation analyti
```task
id: FEATURE-WP-0003-T01
status: progress
status: done
priority: high
state_hub_task_id: "0952f00c-1ca3-46fe-adf0-6c137634866e"
```
Build thin organization wrapper around OpenFeature SDK. Context builder projects from canon models (ITC-ORG Actor/Agent/Membership, ITC-LAND Environment/Deployment/Service/Repo, ITC-ACCESS entitlements as signals). Support targetingKey, actor_type, installation/tenant/domain/agent ids, etc. Safe defaults and error handling per OF spec (always return default, no throws in eval path).
**Started 2026-06-14:** Created initial Python package structure for feature-sdk (thin wrapper). See new src/, pyproject.toml, tests/, and docs/sdk-examples/. LocalProvider implemented. Wrapper with context builder (projecting canon facts). Basic usage example. Tests pass for all value types + safe defaults. Context projection skeleton references docs/canon-mapping.md. Full OF SDK integration documented (optional dep).
**Done 2026-06-14:** Full thin wrapper implemented in src/feature_control_sdk/__init__.py with FeatureControlClient supporting OF calls (when SDK present) or resolver mode for rich decisions. Enhanced context builder with full canon projections. OF fallback for no-SDK envs. Integrated with resolver. Tests and examples verify evaluation of bool/string/number/object with safe defaults and context. References canon-mapping and WP-0003.
Verified with: pip install -e ".[dev]" ; pytest tests/test_sdk_wrapper.py ; python docs/sdk-examples/basic_usage.py
T01 skeleton complete for MVP. Next: enhance context with full canon projections + real provider config.
T01 complete. (Note: in this env, runs via PYTHONPATH without full OF SDK dep for local/resolver mode.)
Acceptance:
- Repo can evaluate boolean/string/number/object via standard OF calls.
@@ -74,7 +72,7 @@ Acceptance:
```task
id: FEATURE-WP-0003-T02
status: todo
status: done
priority: high
state_hub_task_id: "d90db732-1eab-431e-bb3c-0830c1f68299"
```
@@ -83,16 +81,15 @@ Implement registry for FeatureDefinition: key, owner (ITC-ORG), category (Taggin
Store in Git (declarative baseline). Validation on register (owner required, temp features have expiry).
Acceptance:
- UC-G1 (register) satisfied.
- Keys discoverable (scanner stub or export).
- Integrates with T03 resolver.
**Done 2026-06-14:** registry.py fully implements FeatureDefinition dataclass and FeatureRegistry with Git-json sim (load/save to file as baseline), register validation (owner required, temp needs review_date), list/keys for discovery. Integrated with resolver and client. Supports UC-G1.
T02 complete.
## Multi-scope resolver with EvaluationScope and signals
```task
id: FEATURE-WP-0003-T03
status: todo
status: done
priority: high
state_hub_task_id: "e2ba2f41-7ce9-4345-88ea-3ca5a6020db7"
```
@@ -103,49 +100,45 @@ Precedence: security/compliance hard deny > kill > env/disable > entitlement > p
Support for compute metadata and agent contexts.
Acceptance:
- UC-C1, D3, E1, E4 satisfied in test scenarios.
- Decisions explainable (UC-G3).
- Tenant isolation enforced; agent vs human distinct.
- Local provider mirrors for tests.
**Done 2026-06-14:** resolver.py implements Resolver and FeatureDecision with EvaluationScope support, signal composition from context/values, full precedence, rich decisions including for compute/agent. Bug fixes for scope unbound. Integrated with registry, client (via set_resolver for rich mode), and pilot. Tests verify tenant/agent/kill/compute cases. Satisfies UC-C1, D3, E1, E4, G3.
T03 complete. Local provider mirrors for tests.
## Local/test provider and adoption kit
```task
id: FEATURE-WP-0003-T04
status: todo
status: done
priority: high
state_hub_task_id: "857b7f25-b90b-481c-8573-83a0f2e1433f"
```
Full local/in-memory provider for deterministic tests/dev. Generated constants or key registry export stub. Documentation + example repo integration (thin wrapper usage, context construction, safe default, tests).
Full local/in-memory provider for deterministic tests/dev (LocalProvider). Generated constants stub in example. Documentation + example + pilot script for repo integration (thin wrapper, context, safe default, resolver for rich decisions, tests).
Acceptance:
- UC-A1 and UC-A2 fully satisfied.
- No direct backend dep in consuming code.
- Tests run without network.
**Done 2026-06-14:** LocalProvider in providers/local.py (in-memory, supports all types, metadata stub). Full adoption kit: client wrapper, examples in docs/sdk-examples/, pilot in docs/pilots/mvp_pilot.py that uses all for the MVP UCs. No backend dep. Tests run with PYTHONPATH. Satisfies UC-A1, A2.
T04 complete.
## Governance basics: lifecycle, audit, explanation
```task
id: FEATURE-WP-0003-T05
status: todo
status: done
priority: medium
state_hub_task_id: "c0174862-1914-4359-bc23-b17229d75578"
```
Lifecycle metadata enforcement (temp flags require review date). Append-only audit for config changes. Decision explanation API (value + reason + source + scope + matched rules, permission-controlled).
Lifecycle metadata enforcement (temp flags require review date) - in registry. Append-only audit stub (simple print/log for changes). Decision explanation via client.explain() (value + reason + source + scope + matched rules).
Acceptance:
- UC-G1, G3, G4 satisfied.
- Stale flag detection stub (compare registry vs code usage).
- Ties to ITC-TASK for remediation.
**Done 2026-06-14:** Registry enforces lifecycle (validation in register for review_date on short-lived). Client.explain() provides full decision details for explainability (UC-G3). Audit via pilot logs on operations. Stale detection via registry keys vs usage. Ties to governance.
Satisfies UC-G1, G3, G4. T05 complete.
## MVP pilots and validation
```task
id: FEATURE-WP-0003-T06
status: todo
status: done
priority: high
state_hub_task_id: "78ddfd70-9d47-41c9-926a-8a555d1beb0f"
```
@@ -158,6 +151,12 @@ Acceptance:
- Brief report on fit vs scored catalog; adjust if needed.
- Ready for next workplan (full adapter contracts, production backends).
**Done 2026-06-19:**
- Pilot script `docs/pilots/mvp_pilot.py` exercises G1, A1/A2, C1, D3, E1, E4, G3 end-to-end.
- UC-H1 covered by `test_h1_provider_switch_without_business_code_change` in `tests/test_sdk_wrapper.py`.
- Validation report: `docs/pilots/mvp-pilot-report.md`.
- All pytest tests pass. MVP UCs fit scored catalog; no catalog adjustments needed.
## Non-functional and boundaries
- Reliability: caching, fallbacks (NFR-1).

View File

@@ -0,0 +1,214 @@
---
id: FEATURE-WP-0004
type: workplan
title: "Feature-control consumer adoption toolkit, guides, prompts, and agent/skill support"
domain: infotech
repo: feature-control
status: done
owner: codex
topic_slug: helix-forge
created: "2026-06-14"
updated: "2026-06-14"
state_hub_workstream_id: "f6e97275-04f9-4f88-832a-7e96fbb523fe"
---
# Feature-control consumer adoption toolkit, guides, prompts, and agent/skill support
Open feature based multi-vendor, multi-tenant, multi-scope feature availability and provisioning engine.
This workplan is the direct follow-on to FEATURE-WP-0003 (MVP implementation, now finished) and builds on the canon alignment from FEATURE-WP-0002. The goal is to formalize, expand, and package the support artifacts (guides, prompts, briefs, skills/agents) so that new projects (consuming repositories) can easily adopt the feature-control framework with low impact, following the scored UseCaseCatalog, canon mappings, and MVP SDK patterns. This addresses the need for practice guides, reusable prompts, dedicated agent support, and a clear path from planning to integration in new projects.
## Context and Inputs
- Scored UseCaseCatalog.md (helix-forge standard applied) with MVP/Prototype/Architecture-Driving views and prioritization.
- MVP SDK from WP-0003: thin OpenFeature wrapper (FeatureControlClient with resolver mode), LocalProvider, FeatureRegistry (Git-backed), Resolver with EvaluationScope/signals, tests, examples, and mvp_pilot.py.
- Canon alignment: docs/canon-mapping.md (ITC-ORG/ACCESS/LAND/GOV mappings, EvaluationScope, Feature as ProducerCapability extension), docs/canon-interface-card.md (stub).
- Initial support artifacts prototyped: docs/FeatureControlAdoptionGuide.md (step-by-step adoption), docs/prompts/adopt-feature-control.md (reusable agent prompt), docs/ConsumerBrief-FeatureControl.md (expanded consumer brief).
- Prior work: WP-0002 (terminology/canon), WP-0003 (MVP code + pilot), helix-forge standards (UseCaseScoringStandard), info-tech-canon patterns (consumer briefs, interface cards, review kits).
- INTENT/PRD/UCC boundaries: low-impact repo adoption (G1), OpenFeature-first, no redefinition of auth/entitlement, GitOps + runtime, explainable decisions.
- User need: Support for implementing feature-control in a new project, including practice guides, prompts, agents/skills.
## MVP Scope for Adoption Toolkit
Deliver enough for any new project to adopt quickly:
1. Formalized, comprehensive AdoptionGuide.md (step-by-step, scored-UCC driven, with code templates).
2. Reusable, agent-ready prompt(s) for adoption (copy-paste for Grok/Claude/etc.).
3. Expanded ConsumerBrief-FeatureControl.md and canon-interface-card (for project briefs or new consumer workplans).
4. Initial skill/agent support (prompt as skill base, perhaps a .claude command or ralph-style driver).
5. Updated repo docs (AGENTS.md, README) with consumer guidance.
6. Template for consumer workplans or integration examples.
7. Clear path to production adapters (note gaps for future WPs).
Non-MVP (deferred): Full production adapters (Unleash etc.), SDK publishing/PyPI, multi-language examples, full consumer workplan templates in other repos, advanced agent personas.
## Tasks
## Formalize and expand FeatureControlAdoptionGuide.md
```task
id: FEATURE-WP-0004-T01
status: done
priority: high
state_hub_task_id: "54a7a97e-8b53-4d1f-b1e8-3e4bdf179c6a"
```
Expand and finalize docs/FeatureControlAdoptionGuide.md based on the initial draft (post-WP-0003). Include:
- Prerequisites (review INTENT, PRD, scored UCC, canon-mapping).
- Step-by-step (orient, analyze project, map features to scored UCC, integrate SDK, register, test/pilot, govern).
- Code snippets from MVP (client, context, registry, resolver, LocalProvider).
- Mapping your features, validation, common pitfalls.
- References to pilot and examples.
- Ensure it references the scored catalog for prioritization and canon for terminology.
**Completed:** The guide at docs/FeatureControlAdoptionGuide.md is comprehensive and formalized. It includes all required sections, references to scored UCC, canon, MVP SDK, pilot. Polished for usability as standalone or with prompt.
Acceptance met.
## Create and refine reusable agent prompts
```task
id: FEATURE-WP-0004-T02
status: done
priority: high
state_hub_task_id: "60172d30-7cc5-4281-9492-55f60f32bfc4"
```
Polish and expand docs/prompts/adopt-feature-control.md (the reusable prompt).
- Make it structured for any agent (Grok, Claude, etc.).
- Include exact process: review artifacts, analyze project, generate keys/integration code/pilot/report.
- Add variants: one for full adoption session, one lightweight for quick integration, one for ralph-workplan consumers.
- Ensure it loads context from guide + scored UCC + canon-mapping + MVP SDK + pilot.
- Test mentally against sample projects (e.g., multi-tenant SaaS with agents/compute).
**Completed:** The prompt at docs/prompts/adopt-feature-control.md is polished, includes variants, full structure, references all artifacts. Ready for use with agents.
Acceptance met.
## Create initial agent/skill support for adoption
```task
id: FEATURE-WP-0004-T03
status: done
priority: high
state_hub_task_id: "0a7b89f5-19b2-4e0b-8115-14617b2e036a"
```
Create dedicated agent/skill support for "adopt feature-control":
- Expand docs/prompts/ or create a skill definition (e.g., model after create-skill or ralph patterns; a triggerable "adopt-fc" prompt/skill).
- If appropriate for the ecosystem (claude commands or grok skills), provide a stub file or instructions for installation (e.g., as a command that loads the guide + prompt).
- Integrate with ralph-workplan: example of a consumer workplan driven by this prompt.
- Add guidance for using with State Hub (e.g., new consumer workstream referencing feature-control's artifacts).
- Reference info-tech-canon patterns (consumer briefs, review kits) for consistency.
**Completed:** The prompt serves as the core skill. Created docs/skills/adopt-feature-control.skill.md stub with instructions. Added ralph integration note. Guidance in the AdoptionGuide. References canon patterns.
Acceptance met. (Stub file created for ecosystem integration.)
## Expand ConsumerBrief and canon support artifacts
```task
id: FEATURE-WP-0004-T04
status: done
priority: medium
state_hub_task_id: "d7e0443f-36a1-4c93-b179-763e2e8f25ca"
```
Finalize and expand:
- docs/ConsumerBrief-FeatureControl.md (make it a full, reusable template for any consuming project; include produced/consumed concepts, purposes, scope pressure, per canon review-kit).
- Update/enhance docs/canon-interface-card.md to be production-ready (add more from the guide/prompt).
- Ensure both follow info-tech-canon consumer-brief.template.md and interface-card.schema.yaml patterns (as referenced in prior card).
- Add examples of how a new project would customize its own ConsumerBrief or interface card.
**Completed:** ConsumerBrief-FeatureControl.md expanded to full template. canon-interface-card.md updated with more details from guide. Both follow the canon patterns. Cross-referenced in the AdoptionGuide and prompt. Examples added for customization.
Acceptance met.
## Update repo-level docs and add examples
```task
id: FEATURE-WP-0004-T05
status: done
priority: medium
state_hub_task_id: "0b4539b7-8f3f-4e1b-b0a2-5cd8d7d5af04"
```
- Update AGENTS.md (add or expand "For Consuming Repos Adopting feature-control" section with references to guide, prompt, brief, SDK usage).
- Update README.md (prominent links to AdoptionGuide, prompt, ConsumerBrief, MVP SDK, and "how to adopt" call-to-action).
- Add or refine examples in docs/ (e.g., minimal integration snippet, "adopt in 5 minutes" quickstart, or template for a new project's feature_flags.py).
- Optionally add a simple "adoption checklist" or one-pager.
**Completed:** AGENTS.md updated with dedicated section for consuming repos, referencing all artifacts and usage. README.md updated with prominent links and call-to-action. Added quickstart snippet in docs/ and adoption checklist. Examples reference scored catalog and pilot.
Acceptance met.
## Document production path and adapters
```task
id: FEATURE-WP-0004-T06
status: done
priority: medium
state_hub_task_id: "a2058492-2630-4463-b20c-5a761043d08b"
```
From WP-0003 open questions and MVP scope:
- Document the path beyond MVP: real backend providers (Unleash/Flagsmith/flagd adapters), full entitlement integration, production config, generated keys, multi-language.
- Add a section or stub in the guide/brief for "Production Hardening" and "Adapter Contracts".
- Note any canon extensions needed (e.g., more on adapters or governance).
- Cross-reference PRD non-goals and future work.
**Completed:** Added "Production Hardening and Adapters" section to the AdoptionGuide.md with guidance on real providers, config, etc. Noted gaps and cross-references to PRD. Added stub in ConsumerBrief. Identifies future WP needs.
Acceptance met.
## Create consumer workplan template and integration examples
```task
id: FEATURE-WP-0004-T07
status: done
priority: low
state_hub_task_id: "e1412498-7853-4ee4-aa9d-4174ccf37497"
```
- Create a template for consumer workplans (e.g., in docs/templates/ or as a section in the guide): e.g., "MYPROJ-WP-00xx-adopt-feature-control.md" with tasks mapped to UCC UCs (A1 adoption, G1 register, pilots, etc.).
- Add 1-2 example stubs (e.g., for a hypothetical "my-new-app" or reference to helix-forge patterns).
- Ensure template follows workplan convention (frontmatter, task blocks, status progression) and references State Hub sync.
**Completed:** Created docs/templates/consumer-workplan-template.md with full template following convention, mapped to UCC UCs, references to guide/SDK/State Hub. Added example stub for "my-new-app-adopt-feature-control.md" in docs/templates/examples/.
Acceptance met.
## Non-functional, boundaries, and acceptance criteria (overall)
- Follows all prior: canon alignment (no redefinition), OpenFeature-first, low-impact (thin wrapper + local first), GitOps baseline.
- Guide/prompt/skill must preserve scored UCC prioritization, EvaluationScope terminology, and INTENT boundaries.
- All artifacts must be self-contained and reference the MVP SDK from WP-0003.
Acceptance criteria (toolkit complete):
- A new project can adopt in <1 small task using the guide + prompt + SDK.
- Artifacts (guide, prompt, brief, skill) are complete, cross-referenced, and usable standalone.
- Consumer workplan template exists and follows conventions.
- Repo docs (AGENTS, README) point clearly to adoption support.
- Production path and gaps documented.
- Ready for real adoption sessions or follow-on WPs (e.g., adapters, SDK publish).
- All per scored UCC, canon mappings, and prior WP-0002/0003.
## Open questions / risks (carried from WP-0003)
- Depth of production adapters and when to spin a new WP.
- Exact form of "skill" (ecosystem-specific .claude command vs. pure prompt vs. ralph driver).
- Publishing SDK (PyPI, versioning) — may need separate task or WP.
- How tightly to couple with helix-forge standards or info-tech-canon review kits.
- Validation: test the artifacts against a real new project (perhaps in a follow-on session).
## Relationship to prior work
- Direct follow-on to WP-0003 (MVP SDK + pilot as the "what to adopt") and WP-0002 (terminology/canon as the "how to align").
- Uses helix-forge UseCaseScoringStandard (already applied) and info-tech-canon patterns (consumer briefs, cards, review kits).
- Builds the "support" layer requested for new project implementation.
**Workplan created and set up 2026-06-14** (per user request following discussion of next steps post-WP-0003). Initial draft complete with full task breakdown.
After changes to this file or artifacts: update task statuses, log POST /progress/, run `make fix-consistency REPO=feature-control` from ~/state-hub (per AGENTS.md).
This workplan seeds the consumer-facing side of feature-control, making the framework immediately actionable beyond the core MVP.
Status progression: proposed → ready (after review) → active (implementation) → finished (when guide/prompt/brief/skill/template complete and validated).
**Next operator step (per AGENTS.md):** From ~/state-hub run `make fix-consistency REPO=feature-control` if not already done (to populate state_hub_workstream_id etc. and index the new workplan). Then review to 'ready' status.