persistent-memory

name: persistent-memory description: ALWAYS USE THIS SKILL when handling persistent memory in this workspace, including task-start memory recall, explicit "remember" instructions, storing durable preferences/facts, and retrieving prior context. This skill owns the local memory workflow and CLI for init/sync/search/add/recent/stats.

Persistent Memory

Use this skill as the single memory system for this repository.

Commands

Use either command style:

• python3 .agents/skills/persistent-memory/scripts/memory.py <command>
• .agents/skills/persistent-memory/scripts/pmem <command>

Supported commands:

• init
• sync (database-only health check)
• cleanup-legacy
• backfill-embeddings --batch 500
• prune --source "<label>" [--older-than <days>]
• search "<query>" --limit 8
• add "<memory text>" --tags "<comma,tags>" --source "assistant"
• recent --limit 10
• stats

Required Workflow

1. Initialize memory in a fresh workspace:

• pmem init

2. At the start of substantial tasks:

• pmem sync (database-only health check)
• pmem search "<topic keywords>" --limit 8

3. When user explicitly says remember or when a durable preference/fact is learned:

• pmem add "<memory text>" --tags "<tags>" --source "assistant"

4. Before finalizing memory-sensitive work, verify recall state:

• pmem stats

One-Time Migration (If Upgrading From Older Setup)

1. Remove legacy imported rows:

• pmem cleanup-legacy

2. Generate vectors for existing notes:

• pmem backfill-embeddings

Storage Rules

• Store durable preferences, long-lived facts, stable workflows, and repeated constraints.
• Do not store noisy one-off transient details unless requested.
• Keep entries concise and specific.
• Prefer tags that improve retrieval quality (preferences, calendar, comms, product).

Retrieval Rules

• Use targeted search queries instead of broad terms.
• Keep default --limit low unless deeper recall is needed.
• search automatically reinforces recalled entries by updating hits and last_seen_at.
• hits are analytics-oriented and not used as a direct ranking boost.
• Search uses hybrid retrieval: lexical + semantic.
• Semantic search tries sqlite-vec first and auto-falls back to Python cosine if needed.

Bootstrapping and Recovery

• If .memory/ is missing, run pmem init.
• pmem sync is a lightweight database-only check (no markdown import/export).
• If semantic mode degrades, run pmem stats to inspect semantic_backend and embedding_coverage.
• For command examples and quick troubleshooting, read references/usage.md.