Autonomous Memory

When enabled, the agent automatically extracts durable knowledge from past sessions and injects a compact summary into each new session. Over time it builds a project-scoped memory store — technical decisions, recurring workflows, pitfalls — that carries forward without manual effort.

Disabled by default. Enable via /settings or config.yml:

memories:
  enabled: true

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 memory injection payload
clear / reset	Delete all memory data and generated artifacts
enqueue / rebuild	Force consolidation to run at next startup

How it works

Memories are built by a background pipeline that at startup or manually triggered via slash command.

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, or currently active 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 to prevent double-running when multiple processes start simultaneously. Stale skill directories from prior runs are pruned automatically.

All output is scanned for secrets before being written to disk.

Extraction behavior

Memory extraction and consolidation behavior is driven entirely by static prompt files in 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	,
consolidation.md	Prompt for cross-session consolidation	,
read_path.md	Memory guidance injected into live sessions

Model selection

Memory piggybacks on the model role system.

Phase	Role	Purpose
Phase 1 (extraction)	default	Per-session knowledge extraction
Phase 2 (consolidation)	smol	Cross-session synthesis

If smol is not configured, Phase 2 falls back to the default role.

Configuration

Setting	Default	Description
memories.enabled	false	Master switch
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

• src/memories/index.ts — pipeline orchestration, injection, slash command handling
• src/memories/storage.ts — SQLite-backed job queue and thread registry
• src/prompts/memories/ — memory prompt templates
• src/internal-urls/memory-protocol.ts — memory:// URL handler