persistent-memory

Name: persistent-memory
Author: ropl-btc

ALWAYS USE THIS SKILL when handling persistent memory in this workspace, including task-start memory recall, explicit "remember" instructions, storing durable…

INSTALLATION

npx skills add https://github.com/ropl-btc/agent-skills --skill persistent-memory

Run in your project or agent environment. Adjust flags if your CLI version differs.

SKILL.md

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

Initialize memory in a fresh workspace:

pmem init

At the start of substantial tasks:

pmem sync (database-only health check)

pmem search "<topic keywords>" --limit 8

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

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

Before finalizing memory-sensitive work, verify recall state:

pmem stats

One-Time Migration (If Upgrading From Older Setup)

Remove legacy imported rows:

pmem cleanup-legacy

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.