# Review-gate OpenClaw memory hygiene with openclaw-mem

> Pack trusted context and review memory writes before long OpenClaw sessions drift or accumulate low-quality memory.

- Skill: `agentskillexchange/review-gate-openclaw-memory-hygiene-with-openclaw-mem` (Agent Skill)
- Install (CLI): `npx skillmds@latest add agentskillexchange/review-gate-openclaw-memory-hygiene-with-openclaw-mem`
- Raw SKILL.md: https://api.skillmd.com/api/skills/agentskillexchange/review-gate-openclaw-memory-hygiene-with-openclaw-mem/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: agentskillexchange (https://skillmd.com/u/agentskillexchange)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/agentskillexchange/review-gate-openclaw-memory-hygiene-with-openclaw-mem

---


# Review-gate OpenClaw memory hygiene with openclaw-mem

Pack trusted context and review memory writes before long OpenClaw sessions drift or accumulate low-quality memory.

## Prerequisites

OpenClaw, SQLite, local filesystem access

## Installation

Use the upstream install or setup path that matches your environment:
- pip install openclaw-context-pack
- git clone https://github.com/phenomenoner/openclaw-mem.git
- uv sync --locked
- uv run --python 3.13 --frozen -- \

Requirements and caveats from upstream:
- python -m venv .venv
- python benchmarks/trust_policy_synthetic_proof.py --json

Basic usage or getting-started notes:
- **Run the synthetic proof:** [Trust-policy synthetic proof](docs/showcase/trust-policy-synthetic-proof.md)
- **Pack**: run pack to get a bounded bundle_text and context_pack (schema: openclaw-mem.context-pack.v1), with citations, trust policy, and trace receipts.
- openclaw-mem self-curator verify --receipt .state/self-curator/apply-runs/<run>/apply-receipt.json --json

- Source: https://github.com/phenomenoner/openclaw-mem
- Extracted from upstream docs: https://raw.githubusercontent.com/phenomenoner/openclaw-mem/HEAD/README.md

## Documentation

- https://phenomenoner.github.io/openclaw-mem/

## Source

- [Agent Skill Exchange](https://agentskillexchange.com/skills/review-gate-openclaw-memory-hygiene-with-openclaw-mem/)