docs: update SCOPE.md post-0004 + new gap analysis (2026-05-28) vs INTENT.md

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It allows users to express intent in natural language from the terminal and receive safe, explainable, context-aware assistance while keeping memory, history, preferences, and adaptation under explicit user control.
## Current Status (Post CYA-WP-0002 Memory Slice)
## Current Status (Post CYA-WP-0004 Packaging & Distribution Slice)
Two implementation slices have been delivered:
Four implementation slices have been delivered:
- **CYA-WP-0001 (Console-Native MVP)**: Core CLI, context collection, rule-based safety with mandatory confirmation, LLMAdapter seam, and thin memory ports.
- **CYA-WP-0002 (Memory Integration)**: Real user-controlled, persisting memory implementation behind the explicit ports, wired into the orchestrator and `--explain-context`, memory signals integrated into safety, dedicated tests, and documentation.
- **CYA-WP-0001 (Console-Native MVP)**: Core CLI, bounded context collection, rule-based safety with mandatory confirmation, LLMAdapter Protocol seam, basic orchestrator.
- **CYA-WP-0002 (Memory Integration)**: Real user-controlled, persisting memory (scoped JSON) behind explicit ports, wired into context and safety.
- **CYA-WP-0003 (Contextual Activation & Retrospection)**: Directory/project-bound automatic memory activation, `cya retrospect` guided reflection sessions, retrospection outcomes feeding future behavior (continuous user-driven optimization loop).
- **CYA-WP-0004 (Dev-Head Install & Release Packaging)**: Reliable installation from development head (`make dev-install`, direct `git+` installs), dynamic versioning via `setuptools_scm`, clean distribution package building (`python -m build` + verification), lightweight release process, and supporting documentation/Makefile.
Core capabilities now include:
- Natural language request handling via a clean Typer CLI.
- Bounded, transparent, non-recursive local context collection.
- Genuine rule-based risk classification (now memory-aware) with mandatory terminal confirmation.
- Stable `LLMAdapter` Protocol boundary.
- Real, user-controlled memory for preferences and workflow patterns (scoped JSON backing under `~/.config/cya/memory/`, fully inspectable and user-editable).
- Memory surfaced in explanations and fed into safety decisions.
- A small orchestrator coordinating the pipeline.
- Natural language request handling via clean Typer CLI.
- Bounded, transparent local context collection.
- Genuine rule-based (memory-aware) risk classification with mandatory confirmation.
- Stable `LLMAdapter` Protocol.
- Real, user-controlled, contextually activated memory (directory/project scoped) with retrospection support.
- Automatic memory activation based on working directory/git root.
- `cya retrospect` for structured reflection and goal setting.
- Full developer workflow: dev-head install, testing, building distribution packages, and a documented release process.
- Transparent, inspectable behavior via `--explain-context`.
All LLM interaction flows through the documented adapter seam. Memory flows through explicit ports. No production path bypasses these boundaries.
All LLM interaction flows through the documented adapter seam. Memory flows through explicit ports. Packaging and distribution are now first-class concerns with a clear path forward. No production path bypasses the defined boundaries.
## Owns
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- Autonomous or background execution of commands without explicit user confirmation.
- Deep repository indexing, embeddings, or large-scale content analysis (explicit non-goal of the first slice).
- Voice, speech, phone-bridge, or non-terminal interfaces (future work).
- Packaging, distribution, or multi-platform installers beyond basic editable install.
- Production PyPI publishing and automated release CI (documented process and local tooling exist; actual publication is future work).
- Long-lived conversational REPL or session state (one-shot + very lightweight session only).
## Integrates With
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| Project | Responsibility | Integration Style |
|---------------|-----------------------------------------|------------------------------------|
| `llm-connect` | Provider access, config, token counting, structured responses | Stable `LLMAdapter` Protocol |
| `phase-memory`| User-controlled memory, preferences, history | Explicit ports with real (local JSON) implementation (T02); long-term target is deeper profile-driven integration |
| `phase-memory`| User-controlled memory, preferences, history, profiles, and activation planning | Explicit ports with real (local JSON + contextual activation + retrospection) implementation; long-term target is deeper profile-driven integration |
| State Hub | Work tracking, decisions, coordination | HTTP REST (non-runtime) |
## MVP Scope (CYA-WP-0001)
## Current Delivered Scope (Post 0004)
What was explicitly in scope for the first slice:
Significant slices have been delivered beyond the original MVP:
- A functional `cya` CLI that accepts natural language requests.
- Safe, bounded context collection with full transparency (`--explain-context`).
- Rule-based safety classification as the primary mechanism, with mandatory confirmation.
- A clean, documented adapter boundary for future real LLM backends.
- Real user-controlled memory implementation (scoped, persisting, explainable) behind the explicit ports, with a clean seam for future deeper `phase-memory` integration.
- Basic orchestrator that ties the pieces together.
- Test coverage focused on safety invariants and context rules.
- Clear public boundaries and extension points.
- Full console-native CLI with rich output.
- Context-aware, directory/project-bound memory activation.
- User-driven retrospection and continuous optimization loops (`cya retrospect`).
- Real, inspectable, user-controlled memory with strong explainability and safety integration.
- Complete developer workflow: installation from dev head, testing, building distribution packages, and a documented release process.
- Packaging and distribution now treated as first-class concerns (with registered future work).
See the individual workplans for detailed scope per slice.
## Explicitly Out of Scope (Current and Near-Term)
- Full deep integration with the complete `phase-memory` profile/planner/graph system (current implementation uses a deliberate, user-visible local JSON store as the first real backing; deeper integration is planned future work).
- Real `llm-connect` client (only the contract + fake exists).
- Deep git/repository understanding beyond basic status + log + user-declared memory.
- Automatic command execution (even "safe" suggestions).
- Structured editing / patch generation.
- Rich multi-turn conversational state (one-shot + lightweight scoped memory only).
- Full deep integration with the complete `phase-memory` profile/planner/graph system (current implementation uses a deliberate, user-visible local JSON store with contextual activation; deeper integration is planned future work per MemoryVision.md).
- Real `llm-connect` client implementation (only the stable `LLMAdapter` Protocol contract + FakeLLMAdapter exists).
- Deep semantic repository understanding or large-scale content analysis.
- Automatic command execution (even "safe" suggestions) — explicit user confirmation remains mandatory for anything non-safe.
- Rich multi-turn conversational state beyond lightweight scoped memory + retrospection.
- Cost tracking, token budgeting, or usage dashboards.
- Team/shared memory or collaboration features.
- Plugin system or domain-specific extensions.
- Production PyPI publishing and fully automated release CI (a lightweight documented local process exists; automation is future work).
## Extension Points (Registered)
- `cya/llm/adapter.py``LLMAdapter` Protocol (the primary seam).
- `cya/memory/__init__.py` — the four explicit ports with real (persisting, user-controlled) implementation behind them.
- `cya/safety/risk.py` — the `_RULES` table and `classify()` function.
- `cya/memory/__init__.py` — the explicit ports (with real implementation, contextual activation, and retrospection support).
- `cya/safety/risk.py` — the `_RULES` table and `classify()` function (memory-aware).
- `cya/context/collector.py` — collection functions and ignore policy.
- `cya/orchestrator.py` — the main coordination entry point.
- Packaging & distribution: `Makefile`, `pyproject.toml`, `docs/release-process.md`, and `MANIFEST.in` (first-class concern with registered future work).
## Success Criteria (Current Slice)
## Success Criteria (Current State)
A new user can:
- Clone the repo, run `pip install -e .`, and successfully use `cya` for 23 realistic tasks after reading only the README.
- Understand exactly what context is being sent via `--explain-context`.
A new user or contributor can:
- Install the latest development code easily (`make dev-install` or direct git+) and use `cya` for realistic tasks after reading the README.
- Understand exactly what context and memory influenced a response via `--explain-context`.
- Trust that dangerous actions will never execute without explicit confirmation.
- See a clear path for how real `llm-connect` and `phase-memory` will plug in later.
- Use `cya retrospect` to reflect on usage and set goals that influence future behavior.
- Build and verify distribution packages locally.
- See a clear path for how real `llm-connect`, deeper `phase-memory`, and future PyPI releases will integrate.
Sibling project owners can read the workplan + boundary documentation and know precisely where their packages integrate.
Sibling project owners (llm-connect, phase-memory, State Hub) can read the workplans + boundary documentation and know precisely where their packages integrate.
---
**This SCOPE document reflects the state after CYA-WP-0001 (MVP) + CYA-WP-0002 (Memory Integration).**
**This SCOPE document reflects the state after CYA-WP-0004 (Dev-Head Install & Release Packaging).**
It is intentionally narrower than the long-term vision in INTENT.md and MemoryVision.md, but now includes a real first slice of user-controlled memory as delivered by 0002.
It remains intentionally narrower than the long-term vision in INTENT.md and MemoryVision.md, but now incorporates significant advances in contextual memory activation, user-driven retrospection/optimization loops, and proper packaging & distribution capabilities.
See `workplans/CYA-WP-0002-memory-integration-roadmap.md` and `MemoryVision.md` for the intended direction of deeper `phase-memory` integration.
See the individual workplans (especially CYA-WP-0003 and CYA-WP-0004) and `MemoryVision.md` for the intended direction of deeper `phase-memory` integration and future evolution.