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# Autonomous Memory
When the local memory backend is enabled, the agent automatically extracts durable knowledge from past sessions and injects a compact summary into future sessions for the same project. Over time it builds a project-scoped memory store — technical decisions, recurring workflows, pitfalls — that carries forward without manual effort.
Disabled by default. Enable the local summary pipeline via `/settings` or `config.yml`:
```yaml
memory:
backend: local
```
## Usage
### What gets injected
At session start, if a memory summary exists for the current project, it is injected into the system prompt as a **Memory Guidance** block. The agent is instructed to:
- Treat memory as heuristic context — useful for process and prior decisions, not authoritative on current repo state.
- Cite the memory artifact path when memory changes the plan, and pair it with current-repo evidence before acting.
- Prefer repo state and user instruction when they conflict with memory; treat conflicting memory as stale.
### Reading memory artifacts
The agent can read memory files directly using `memory://` URLs with the `read` tool:
| URL | Content |
| -------------------------------------- | ----------------------------------- |
| `memory://root` | Compact summary injected at startup |
| `memory://root/MEMORY.md` | Full long-term memory document |
| `memory://root/skills/<name>/SKILL.md` | A generated skill playbook |
### `/memory` slash command
| Subcommand | Effect |
| --------------------- | --------------------------------------------------------- |
| `view` | Show the current backend injection payload |
| `stats` | Show backend-specific memory statistics, when supported |
| `diagnose` | Show backend-specific diagnostics, when supported |
| `clear` / `reset` | Delete active backend memory data/artifacts |
| `enqueue` / `rebuild` | Force consolidation/retention work for the active backend |
## How it works
Local summary memories are built by a background pipeline that runs at startup; `/memory enqueue` marks consolidation work that the next startup picks up. The pipeline is skipped for subagents and for sessions that are not persisted to a session file.
**Phase 1 — per-session extraction:** For each past session that has changed since it was last processed, a model reads the session history and extracts durable signal: technical decisions, constraints, resolved failures, recurring workflows. Sessions that are too recent, too old, currently active, or beyond the configured scan/age limits are skipped. Each extraction produces a raw memory block and a short synopsis for that session.
**Phase 2 — consolidation:** After extraction, a second model pass reads all per-session extractions and produces three outputs written to disk:
- `MEMORY.md` — a curated long-term memory document
- `memory_summary.md` — the compact text injected at session start
- `skills/` — reusable procedural playbooks, each in its own subdirectory
Phase 2 uses a lease and heartbeat to prevent double-running when multiple processes start simultaneously. Stale skill directories from prior runs are pruned automatically.
Consolidated output is redacted for common secret/token patterns before `MEMORY.md`, `memory_summary.md`, or generated skills are written to disk.
### Extraction behavior
Memory extraction and consolidation behavior is driven by static prompt files in `packages/coding-agent/src/prompts/memories/`.
| File | Purpose | Variables |
| ------------------------ | -------------------------------------------- | ------------------------------------------- |
| `stage_one_system.md` | System prompt for per-session extraction | — |
| `stage_one_input.md` | User-turn template wrapping session content | `{{thread_id}}`, `{{response_items_json}}` |
| `consolidation_system.md`| System prompt for cross-session consolidation | — |
| `consolidation.md` | User-turn prompt for cross-session consolidation | `{{raw_memories}}`, `{{rollout_summaries}}` |
| `read-path.md` | Memory guidance injected into live sessions | `{{memory_summary}}`, `{{learned}}` |
### Model selection
Memory piggybacks on the model role system.
| Phase | Role | Purpose |
| ----------------------- | ------------------------------------------------------------------- | -------------------------------- |
| Phase 1 (extraction) | `default` | Per-session knowledge extraction |
| Phase 2 (consolidation) | `smol` (falls back to `default`, then current/first registry model) | Cross-session synthesis |
If the requested memory role is not configured, memory model resolution falls back to the `default` role, then the active session model, then the first model in the registry.
## Configuration
| Setting | Default | Description |
| ------------------------------------- | ------- | ---------------------------------------------------------------------------------------------------------------------------------------- |
| `memory.backend` | `off` | Select `local` for this pipeline; legacy `memories.enabled: true` is migrated to `memory.backend: local` when no explicit backend is set |
| `memories.maxRolloutAgeDays` | `30` | Sessions older than this are not processed |
| `memories.minRolloutIdleHours` | `12` | Sessions active more recently than this are skipped |
| `memories.maxRolloutsPerStartup` | `64` | Cap on sessions processed in a single startup |
| `memories.summaryInjectionTokenLimit` | `5000` | Max tokens of the summary injected into the system prompt |
Additional tuning knobs (concurrency, lease durations, token budgets) are available in config for advanced use.
## Key files
- `packages/coding-agent/src/memories/index.ts` — pipeline orchestration, injection, clear/enqueue entry points (the `/memory` command routes here via `packages/coding-agent/src/memory-backend/local-backend.ts`)
- `packages/coding-agent/src/memories/storage.ts` — SQLite-backed job queue and thread registry
- `packages/coding-agent/src/prompts/memories/` — memory prompt templates
- `packages/coding-agent/src/internal-urls/memory-protocol.ts``memory://` URL handler