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claude-archeflow-plugin/skills/memory/SKILL.md
Christian Nennemann cccaf86995 refactor: replace 3-Sets diagnostic with focused attention filters and memory
The 3-Sets framework doesn't transfer well to agents — all three
dimensions are fully visible and controllable config, not hidden
human psychology. Removed the branding, kept the practical bits:

- attention-filters: what context each archetype receives (token savings)
- memory: persistent learnings across orchestrations (project knowledge)
2026-04-02 18:36:10 +00:00

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1.9 KiB
Markdown

---
name: memory
description: Use after orchestration to record learnings, and before orchestration to load project-specific context. Persistent knowledge that makes future orchestrations smarter.
---
# Persistent Memory
ArcheFlow learns across orchestrations. After each run, extract what was discovered. Before the next run, load it so agents start smarter.
## What to Record
Store in `.archeflow/memory/project.md`:
```markdown
## Project Context
- Language: TypeScript, strict mode
- Package manager: pnpm
- Test runner: vitest
- CI: GitHub Actions (no DB access in CI)
## Risk Map
- auth/ — well-tested (95% coverage), normal risk
- payment/ — no tests, elevated risk, Guardian should be thorough
- legacy/api-v1/ — deprecated, do not modify
## Model Notes
- Type-heavy modules need Sonnet minimum (Haiku produced incomplete types)
- Standard CRUD reviews work fine with Haiku
## Shadow History
- Explorer rabbit-holed in monorepo (cycle 1 of orchestration on 2026-03-28)
→ added 10-file cap to Explorer prompt for this project
```
## What NOT to Record
- Anything derivable from code or git history
- Temporary state from current orchestration
- Opinions or predictions
- Anything that changes every week
## When to Read
Before orchestration, check if `.archeflow/memory/project.md` exists. If it does, inject relevant sections into agent prompts:
- Explorer gets: Project Context
- Guardian gets: Risk Map
- Maker gets: Project Context
- All agents get: Model Notes (for self-calibration)
## When to Write
After orchestration completes, update memory if anything new was learned:
- New project conventions discovered by Explorer
- Risk areas identified by Guardian
- Model tier adjustments needed (Haiku insufficient, or Opus unnecessary)
- Shadow patterns that recurred
Update existing entries — don't append endlessly. Memory should be a current snapshot, not a changelog.