Files
can-you-assist/SCOPE.md
tegwick cbf66cf967 docs: add AGENTS.md and SCOPE.md as canonical repo instructions
These were part of the initial Grok handoff for the can-you-assist
repo integration workstream (repo-integration-can-you-assist).

- AGENTS.md: Worker protocol, State Hub integration, workplan
  convention, session start/close checklist.
- SCOPE.md: Crisp boundaries (owns CLI + orchestration, does not
  own llm-connect or phase-memory implementations).

Complements the just-added CYA-WP-0001 workplan.
Brings the documented seed state to a complete, committed baseline.

Workstream: 0a1233fd-75ab-4726-8857-6c97de939069
2026-05-26 00:40:52 +02:00

1.8 KiB

Scope: can-you-assist

Purpose

can-you-assist provides cya, a console-native LLM helper for practical local work. It lets a terminal user ask for help in natural language, gather relevant local context intentionally, and receive safe, explainable assistance for command-line, repository, filesystem, note, and text workflows.

Owns

  • The cya command-line user experience.
  • Intent parsing and task framing for local shell work.
  • Local context collection from the current directory, selected files, stdin, git state, logs, notes, and user-provided paths.
  • Safe command suggestion and explanation workflows.
  • Prompt/request orchestration against llm-connect.
  • Local preference and memory usage through phase-memory.
  • Transparent configuration and inspectable local state for this assistant.

Does Not Own

  • Provider-specific LLM clients or vendor credentials; that belongs in llm-connect.
  • Long-term memory storage semantics; that belongs in phase-memory.
  • Global State Hub implementation or workstream indexing.
  • Autonomous shell execution without clear user confirmation.
  • Hidden, vendor-owned personalization or opaque memory.

Integrates With

  • llm-connect for backend-agnostic model access.
  • phase-memory for user-controlled history, preferences, and adaptation.
  • State Hub for work tracking, repo coordination, progress, and decisions.

Initial Direction

The first implementation slice should establish a minimal but real CLI:

  • parse a natural-language request;
  • inspect current working-directory context safely;
  • produce an explainable command or answer;
  • route LLM calls through an adapter boundary shaped for llm-connect;
  • leave memory hooks explicit but thin until phase-memory integration is ready;
  • include tests around command-suggestion safety and context selection.