af3016fe27
Forked from OpenCode v1.17.4 with multi-agent system: - 5 agents: aircoding, scheduler, worker, architect, reviewer - Deterministic DAG scheduling engine (coordinator_tick) - Tool whitelists as hard enforcement - AirCoding validation plugin - System prompt injection for routing - V1 requirements: C4 docs, ADR, AGENTS.md, debug-log.md - Design documents in docs/
1.6 KiB
1.6 KiB
description
| description |
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| Extract non-obvious learnings from session to AGENTS.md files to build codebase understanding |
Analyze this session and extract non-obvious learnings to add to AGENTS.md files.
AGENTS.md files can exist at any directory level, not just the project root. When an agent reads a file, any AGENTS.md in parent directories are automatically loaded into the context of the tool read. Place learnings as close to the relevant code as possible:
- Project-wide learnings → root AGENTS.md
- Package/module-specific → packages/foo/AGENTS.md
- Feature-specific → src/auth/AGENTS.md
What counts as a learning (non-obvious discoveries only):
- Hidden relationships between files or modules
- Execution paths that differ from how code appears
- Non-obvious configuration, env vars, or flags
- Debugging breakthroughs when error messages were misleading
- API/tool quirks and workarounds
- Build/test commands not in README
- Architectural decisions and constraints
- Files that must change together
What NOT to include:
- Obvious facts from documentation
- Standard language/framework behavior
- Things already in an AGENTS.md
- Verbose explanations
- Session-specific details
Process:
- Review session for discoveries, errors that took multiple attempts, unexpected connections
- Determine scope - what directory does each learning apply to?
- Read existing AGENTS.md files at relevant levels
- Create or update AGENTS.md at the appropriate level
- Keep entries to 1-3 lines per insight
After updating, summarize which AGENTS.md files were created/updated and how many learnings per file.
$ARGUMENTS