Digest agent notes, classify them, and promote reviewable documentation drafts — never silent auto-merge.

Memory pipeline

Agent sessions leave durable learnings in local files. Doc Bridge ingests, classifies, and promotes them into draft documentation that humans review. Nothing lands in the corpus without a PR.

Sources (Layer 0)

Source	Path pattern
Agent memory notes	`.agent-memory/*/.md`
Cursor rules	`.cursor/rules/*.mdc`

No API key. Classification is deterministic.

End-to-end commands

# 1) Normalize raw notes → MemoryCandidate[]
ak-docs memory ingest

# 2) Route each candidate: agent | human | playbook | discard
ak-docs memory classify

# 3) Build a safe draft body (safety scan; never auto-merges)
ak-docs memory promote

# 4) Optional: open a GitHub draft PR via `gh`
ak-docs memory promote --pr --dry-run
ak-docs memory promote --pr

What a candidate looks like

{
  "schemaVersion": 1,
  "id": "auth-abort-signal",
  "source": "agent-memory",
  "rawPath": ".agent-memory/auth.md",
  "fact": "Auth handlers must forward AbortSignal.",
  "why": "Run cancellation must stop network work.",
  "howToApply": "Use AbortSignal.any([caller, AbortSignal.timeout(ms)]).",
  "suggestedType": "project",
  "confidence": 0.8,
  "references": ["docs/for-agents/auth.md"]
}

Schema: MemoryCandidate v1

Digest mental model

.agent-memory / .cursor/rules
        │
        ▼
  memory ingest     →  normalized candidates
        │
        ▼
  memory classify   →  agent | human | playbook | discard
        │
        ▼
  memory promote    →  draft markdown (+ optional draft PR)
        │
        ▼
  Human review / merge   (never silent)

Safety guarantees

Guarantee	Behavior
Draft-only	Promotion never writes the canonical corpus directly
Safety scan	Risky content is flagged before draft output
HITL	`--pr` opens a draft GitHub PR via `gh`
Deterministic	Same inputs → same classify/promote routing

MCP tools

When MCP is running (ak-docs mcp):

Tool	Role
`memory.classify`	Classify candidates
`memory.promoteDraft`	Produce a draft promotion body

See MCP for agents.

Playbook feedback

ak-docs playbook draft      # payload from classified memory
ak-docs playbook pattern    # published Doc Bridge pattern (OKF)

CLI map — every command
MemoryCandidate schema
Chat and RAG — optional Layer 1 after handoffs
Getting started