generated from coulomb/repo-seed
chore: register Phase 7 workplan (IHUB-WP-0007)
7 tasks: T01 schema (FrictionScore, BottleneckRecord, HubHealthSnapshot, CrossHubPropagation) → T02 widget pain heatmap → T03 workflow bottleneck analysis → T04 hub health correlation → T05 cross-hub propagation → T06 operational review board → T07 gate. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
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---
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id: IHUB-WP-0007
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type: workplan
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title: "IHF Phase 7 — Advanced Observability and Operational Integration"
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domain: inter_hub
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repo: inter-hub
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status: todo
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owner: custodian
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topic_slug: inter_hub
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created: "2026-03-29"
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updated: "2026-03-29"
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state_hub_workstream_id: "541e06b3-c7ff-4a27-9259-338e04b2aa2f"
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---
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# IHF Phase 7 — Advanced Observability and Operational Integration
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## Goal
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Integrate interaction governance with broader operational intelligence. Phase 6
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established cross-framework widget participation. Phase 7 turns the accumulated
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interaction data into operational intelligence: friction heatmaps, pipeline
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bottleneck detection, per-hub health scores, and cross-hub pattern propagation.
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The capstone is an Operational Review Board dashboard that gives hub leaders a
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unified view across all hubs.
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## Background
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Phases 1–6 are complete. The IHF core (widget registry, interaction events,
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annotations, requirements, decisions, outcomes, agent assistance,
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cross-framework adapters) is stable and extensible.
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The spec (§Phase 7) calls for:
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- Hub health correlation
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- Policy violation correlation
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- Workflow bottleneck analysis
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- Interaction pain heatmaps
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- Queue and job linkage
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- Cross-hub issue propagation analysis
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Artifacts introduced: `FrictionScore`, `BottleneckRecord`, `HubHealthSnapshot`,
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`CrossHubPropagation`.
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Reference: `specs/InteractionHubFrameworkSpecification_v0.1.md` §Phase 7,
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`docs/phase6-summary.md`, `docs/ihp-controllers-views-forms.md`.
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## Phase 7 Exit Criteria (from IHF spec §Phase 7)
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- Interaction data informs operational decision-making
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- Hub leaders can inspect systemic friction patterns
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- The platform supports cross-domain learning
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## Data Artifacts Introduced (Phase 7)
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`FrictionScore`, `BottleneckRecord`, `HubHealthSnapshot`, `CrossHubPropagation`
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---
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## Tasks
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### T01 — Schema: FrictionScore, BottleneckRecord, HubHealthSnapshot, CrossHubPropagation
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```task
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id: IHUB-WP-0007-T01
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status: todo
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priority: high
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state_hub_task_id: "86e31f8b-62a3-4176-9b10-2fe7a8dbcc23"
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```
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Add Phase 7 tables to `Application/Schema.sql` and write migration:
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```sql
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-- Aggregated pain score per widget, recomputed on demand or scheduled.
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CREATE TABLE friction_scores (
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id UUID DEFAULT uuid_generate_v4() PRIMARY KEY NOT NULL,
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widget_id UUID NOT NULL REFERENCES widgets(id),
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score INTEGER NOT NULL DEFAULT 0,
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-- 0–100; higher = more friction
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annotation_count INTEGER NOT NULL DEFAULT 0,
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error_event_count INTEGER NOT NULL DEFAULT 0,
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regression_flag BOOLEAN NOT NULL DEFAULT FALSE,
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stale_candidate_count INTEGER NOT NULL DEFAULT 0,
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last_computed_at TIMESTAMP WITH TIME ZONE DEFAULT now() NOT NULL,
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UNIQUE (widget_id)
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);
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CREATE INDEX friction_scores_widget_id_idx ON friction_scores (widget_id);
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CREATE INDEX friction_scores_score_idx ON friction_scores (score DESC);
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-- Detected stalls at specific pipeline stages.
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CREATE TABLE bottleneck_records (
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id UUID DEFAULT uuid_generate_v4() PRIMARY KEY NOT NULL,
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hub_id UUID NOT NULL REFERENCES hubs(id),
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stage TEXT NOT NULL,
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-- 'candidate' | 'requirement' | 'decision' | 'observation'
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subject_type TEXT NOT NULL,
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-- 'RequirementCandidate' | 'Requirement' | 'DecisionRecord' | 'DeploymentRecord'
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subject_id UUID NOT NULL,
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stalled_since TIMESTAMP WITH TIME ZONE NOT NULL,
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severity TEXT NOT NULL DEFAULT 'medium',
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-- 'low' | 'medium' | 'high' | 'critical'
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resolved_at TIMESTAMP WITH TIME ZONE,
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notes TEXT,
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created_at TIMESTAMP WITH TIME ZONE DEFAULT now() NOT NULL
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);
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CREATE INDEX bottleneck_records_hub_id_idx ON bottleneck_records (hub_id);
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CREATE INDEX bottleneck_records_stage_idx ON bottleneck_records (stage);
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CREATE INDEX bottleneck_records_resolved_idx ON bottleneck_records (resolved_at)
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WHERE resolved_at IS NULL;
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-- Periodic health snapshots for trend tracking.
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CREATE TABLE hub_health_snapshots (
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id UUID DEFAULT uuid_generate_v4() PRIMARY KEY NOT NULL,
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hub_id UUID NOT NULL REFERENCES hubs(id),
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health_score INTEGER NOT NULL,
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-- 0–100
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open_candidates INTEGER NOT NULL DEFAULT 0,
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regressed_widgets INTEGER NOT NULL DEFAULT 0,
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stale_decisions INTEGER NOT NULL DEFAULT 0,
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active_bottlenecks INTEGER NOT NULL DEFAULT 0,
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computed_at TIMESTAMP WITH TIME ZONE DEFAULT now() NOT NULL
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);
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CREATE INDEX hub_health_snapshots_hub_id_idx ON hub_health_snapshots (hub_id);
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CREATE INDEX hub_health_snapshots_computed_at_idx
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ON hub_health_snapshots (hub_id, computed_at DESC);
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-- Patterns detected across multiple hubs.
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CREATE TABLE cross_hub_propagations (
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id UUID DEFAULT uuid_generate_v4() PRIMARY KEY NOT NULL,
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pattern_type TEXT NOT NULL,
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-- 'annotation_cluster' | 'widget_type_friction'
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source_hub_id UUID REFERENCES hubs(id),
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affected_hub_ids JSONB NOT NULL DEFAULT '[]',
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-- array of hub UUIDs
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summary TEXT NOT NULL,
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detected_at TIMESTAMP WITH TIME ZONE DEFAULT now() NOT NULL,
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status TEXT NOT NULL DEFAULT 'open',
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-- 'open' | 'acknowledged' | 'resolved'
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notes TEXT
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);
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CREATE INDEX cross_hub_propagations_status_idx ON cross_hub_propagations (status);
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CREATE INDEX cross_hub_propagations_pattern_idx ON cross_hub_propagations (pattern_type);
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```
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**Exit criteria:** `migrate` runs cleanly; all Phase 7 types available in GHCi.
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---
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### T02 — Widget Pain Heatmap: friction scoring and per-hub heatmap view
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```task
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id: IHUB-WP-0007-T02
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status: todo
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priority: high
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state_hub_task_id: "3a5ecd28-17c2-4258-bfd9-b3eaecf52135"
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```
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1. Add `Application/Helper/FrictionScore.hs` with `computeFrictionScore`:
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- `annotation_count` — total annotations for widget
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- `error_event_count` — events with `event_type = 'errored'`
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- `regression_flag` — `True` if widget appears in `regressedWidgetIds`
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- `stale_candidate_count` — open candidates older than 30 days
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- Score formula (documented in module header):
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```
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score = min 100 $
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annotationCount * 5
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+ errorEventCount * 10
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+ (if regressionFlag then 20 else 0)
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+ staleCandidateCount * 8
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```
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- Upserts into `friction_scores` (UPDATE if exists, INSERT otherwise)
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2. Add `RecomputeFrictionAction { hubId }` to `HubsController`:
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- Recomputes scores for all widgets in the hub
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- Redirects back to heatmap view
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3. Add `FrictionHeatmapAction { hubId }` view:
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- Grid of widget cards, colour-coded by score band:
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- 0–19: green (`bg-green-100`)
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- 20–39: yellow (`bg-yellow-100`)
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- 40–59: amber (`bg-orange-100`)
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- 60+: red (`bg-red-100`)
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- Each card: widget name, score, link to widget show
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- "Recompute" button triggers `RecomputeFrictionAction`
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4. Link from hub Show page as "Friction Heatmap"
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**Exit criteria:** Scores compute correctly for test fixtures; heatmap renders
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with correct colour bands; recompute updates scores.
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---
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### T03 — Workflow Bottleneck Analysis: stall detection across the pipeline
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```task
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id: IHUB-WP-0007-T03
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status: todo
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priority: high
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state_hub_task_id: "ada0347a-880b-454e-843f-4a9135ea8739"
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```
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1. Add `Application/Helper/BottleneckDetector.hs` with `detectBottlenecks`:
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- Stage 1 — `candidate`: `RequirementCandidate` with `status='open'` and
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`created_at < now() - interval '30 days'`
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- Stage 2 — `requirement`: `Requirement` with no linked `DecisionRecord` and
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`created_at < now() - interval '60 days'`
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- Stage 3 — `decision`: `DecisionRecord` with no linked `DeploymentRecord`
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and `decided_at < now() - interval '30 days'`
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- Stage 4 — `observation`: `DeploymentRecord` with no linked `OutcomeSignal`
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and `deployed_at < now() - interval '14 days'`
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- Severity: `critical` if age > 2× threshold, else `high` if > 1.5×, else `medium`
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- Upserts `BottleneckRecord` (skip if already exists for same subject)
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2. Add `DetectBottlenecksAction { hubId }` — runs detector, redirects to dashboard
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3. Add `BottleneckDashboardAction { hubId }` view:
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- Table grouped by pipeline stage
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- Columns: subject (linked), stalled since, age, severity badge
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- "Resolve" button → `ResolveBottleneckAction { bottleneckRecordId }`
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- "Detect" button triggers fresh detection
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4. Link from hub Show page as "Bottlenecks"
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**Exit criteria:** Stale candidates create bottleneck records; dashboard renders
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and groups correctly; resolve marks `resolved_at`.
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---
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### T04 — Hub Health Correlation: composite health score and history
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```task
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id: IHUB-WP-0007-T04
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status: todo
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priority: high
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state_hub_task_id: "b0c932c5-fdb7-47b6-adc7-b4f8ed5555e6"
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```
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1. Add `Application/Helper/HubHealth.hs` with `computeHubHealth`:
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- Deduction table (documented in module):
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```
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-5 per open RequirementCandidate
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-10 per regressed widget
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-8 per stale DecisionRecord (decided > 30 days, no deployment)
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-12 per active critical BottleneckRecord
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-6 per active high BottleneckRecord
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floor at 0
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```
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- Inserts new `HubHealthSnapshot` (never updates — history is append-only)
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2. Add `SnapshotHubHealthAction { hubId }` — computes and redirects to history
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3. Add `HubHealthHistoryAction { hubId }` view:
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- Table of snapshots: timestamp, score (colour-coded), component breakdown
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- Latest score shown prominently at top
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4. Show health score badge on hub Show page (next to dashboard links):
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- Fetch latest snapshot; display colour-coded score pill
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- If no snapshot: "–" with link to take first snapshot
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**Exit criteria:** Snapshot computes correct score against test fixtures; history
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table renders in order; badge appears on hub Show page.
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---
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### T05 — Cross-Hub Propagation Analysis: pattern detection across hubs
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```task
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id: IHUB-WP-0007-T05
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status: todo
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priority: medium
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state_hub_task_id: "7a860b9f-a835-47d6-96d8-2964ae37b12d"
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```
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1. Add `Application/Helper/CrossHubPropagation.hs` with `detectPropagations`:
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- **Annotation cluster heuristic**: for each annotation `category`, count
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distinct hubs with ≥3 annotations in that category in the last 14 days.
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If ≥2 hubs qualify, emit a `CrossHubPropagation` with
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`pattern_type='annotation_cluster'` and a generated summary.
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- **Widget type friction heuristic**: for each `widget_type`, count hubs
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where the max `FrictionScore` for that type is ≥40. If ≥2 hubs qualify,
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emit `pattern_type='widget_type_friction'`.
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- Skip if a matching open/acknowledged propagation already exists
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(idempotent detection)
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2. Add `DetectPropagationsAction` (global, no hubId) — runs detector
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3. Add `CrossHubPropagationsAction` view (global):
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- Table: pattern type, source hub, affected hubs (comma list), summary,
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detected at, status badge
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- "Acknowledge" and "Resolve" actions
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4. Link from global nav (alongside "Adapters", "Ops Review")
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**Exit criteria:** Detection creates propagation records for qualifying patterns;
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duplicate runs are idempotent; acknowledge/resolve transitions work.
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---
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### T06 — Operational Review Board Dashboard: cross-hub unified view
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```task
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id: IHUB-WP-0007-T06
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status: todo
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priority: medium
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state_hub_task_id: "ffabc4d1-c166-4b7d-8bec-55365cbe0666"
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```
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1. Add `OperationalReviewBoardAction` to a new `OperationsController`
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(or `HubsController` as a global action — no `hubId` parameter):
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- **Panel 1 — Hub health matrix**: all hubs, latest health score (or "–"),
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colour-coded row, link to hub and to health history
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- **Panel 2 — Top friction widgets**: top 10 across all hubs by
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`FrictionScore.score DESC`; columns: widget name, hub, score band, link
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- **Panel 3 — Active bottlenecks by stage**: count of unresolved bottlenecks
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per stage across all hubs; click-through to hub bottleneck dashboard
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- **Panel 4 — Open cross-hub propagations**: list of open/acknowledged
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propagation events with pattern type and affected hub count
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2. `autoRefresh` — live-updates
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3. Link from global nav as "Ops Review"
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4. Link from global nav cross-hub propagation count badge if > 0
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**Exit criteria:** Dashboard renders all four panels; health matrix shows all
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hubs; top friction list is correctly sorted; live-updates on data change.
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---
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### T07 — Phase 7 gate: tests, consistency, docs
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```task
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id: IHUB-WP-0007-T07
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status: todo
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priority: high
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state_hub_task_id: "a14b94f8-3b27-4f0c-9949-60fb65a57a05"
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```
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1. **Integration tests** (`Test/`):
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- `FrictionScore` compute formula: widget with known annotation count →
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expected score
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- `BottleneckRecord` create + resolve: stale candidate → bottleneck detected;
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resolve sets `resolved_at`
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- `HubHealthSnapshot` compute: hub with known candidates/regressions → expected
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score; history fetch returns in order
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- `CrossHubPropagation` create + acknowledge + resolve
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- `OperationalReviewBoard` action: compiles, fetches all hubs, returns counts
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2. **Consistency sync** via State Hub MCP:
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`check_repo_consistency(repo_slug="inter-hub", fix=True)`
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3. **Documentation updates:**
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- Update `SCOPE.md` current state section: Phase 7 complete
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- Write `docs/phase7-summary.md`: what was built, scoring formulae, bottleneck
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thresholds, cross-hub heuristics, known limitations, Phase 8 readiness
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4. **Smoke test checklist:**
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- Create two hubs with widgets and annotations; run friction recompute; verify
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heatmap colours
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- Age a candidate by force-setting `created_at`; run detect bottlenecks;
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verify record appears
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- Snapshot health for both hubs; verify Ops Review Board health matrix
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- Trigger cross-hub propagation detection; verify propagation record
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- Open Ops Review Board; confirm all four panels populate
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**Exit criteria:** All tests pass; consistency sync reports no errors; smoke
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test completed; SCOPE.md updated.
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---
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## Phase 7 Dependencies
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- Phases 1–6 schema stable (widget registry, interaction events, annotations,
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requirements, decisions, outcomes, agent proposals, adapter specs)
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- `friction_scores` requires widgets (T01 before T02)
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- `bottleneck_records` requires hubs, candidates, requirements, decisions,
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deployments (T01 before T03)
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- `hub_health_snapshots` requires hubs and reads from bottleneck_records
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(T03 before T04)
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- `cross_hub_propagations` requires hub friction scores (T02 before T05)
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- Operational Review Board aggregates all Phase 7 data (T02–T05 before T06)
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- All feature tasks (T01–T06) before gate (T07)
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## Notes
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- **Friction scores are recomputed, not append-only.** Each widget has at most
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one `FrictionScore` row (unique constraint on `widget_id`). Historical trend
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is not tracked at the friction level — use `HubHealthSnapshot` for trends.
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- **Bottleneck detection is idempotent.** Re-running the detector skips records
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where an unresolved bottleneck already exists for the same subject.
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- **Health snapshots are append-only.** Every `SnapshotHubHealthAction` call
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inserts a new row. This preserves the health history for trend analysis.
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- **Cross-hub detection requires FrictionScores to be current.** Run
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`RecomputeFrictionAction` for all hubs before `DetectPropagationsAction`.
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- **No scheduled jobs in Phase 7.** Detection and recomputation are triggered
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manually via UI or curl. Phase 8 can layer on a cron/job system.
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- **Severity thresholds and score weights are constants in the helper modules.**
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They are intentionally not stored in the DB to avoid config drift — change
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them in code and recompute.
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Block a user