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

47 lines
1.8 KiB
Markdown

# 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.