---
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.