Agent skill · AI & Agents

add-mnemon

Add persistent graph-based memory via mnemon. Agents recall past context before responding and remember insights after each turn.

NanoCo30,389★ · +78/wk · 1 repos on radarProfile →
claude-codeships scriptsMIT
Install
npx skills add nanocoai/nanoclaw --skill add-mnemon --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 4
SKILL.md size: 7 KB
Bundled scripts: yes
Path: .claude/skills/add-mnemon/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 30,426 · +37 this week
Language: TypeScript
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Add Mnemon — Persistent Memory Installs [mnemon](https://github.com/mnemon-dev/mnemon) in the agent container image. On each container start, `mnemon setup` registers Claude Code hooks that surface relevant memory before the agent responds and store new insights after each turn. Memory is written to the per-agent-group `.claude/` mount and survives container restarts. ## Provider Compatibility mnemon hooks fire only under `--target claude-code`. Use this skill on agent groups that run the default Claude provider. The provider is the materialized `provider` key in each group's `container.json` (absent or `claude` = default Claude provider). Confirm it before applying: ```bash grep -H '"provider"' groups/*/container.json 2>/dev/null # no match, or "provider": "claude" = Claude ``` If a group sets a different provider (e.g. `"provider": "opencode"`), it spawns its own process and never invokes the `claude` CLI, so the hooks registered by `mnemon setup` do not run for that group. ## Phase 1: Pre-flight ### Check if already applied ```bash grep -q 'MNEMON_VERSION' container/Dockerfile && echo "Already applied" || echo "Not applied" ``` If already applied, re-run Phase 2 anyway — every

What's inside
Steps it walks through
  1. Provider Compatibility
  2. Phase 1: Pre-flight
  3. Check if already applied
  4. Check latest mnemon version
  5. Phase 2: Apply Changes
  6. 1. Dockerfile — install mnemon binary
  7. 2. Entrypoint — run mnemon setup on each container start
  8. 3. Copy the integration tests
  9. 4. Rebuild and smoke-test the image
  10. Phase 3: Restart and Verify
  11. Restart the service
  12. Confirm mnemon hooks are registered
  13. Test memory recall
  14. Memory Storage
Ships with 3 files
  • REMOVE.md
  • mnemon-dockerfile.test.ts
  • mnemon-entrypoint.test.ts
Commands it runs
grep -H '"provider"' groups/*/container.json 2>/dev/null   # no match, or "provider": "claude" = Claude
grep -q 'MNEMON_VERSION' container/Dockerfile && echo "Already applied" || echo "Not applied"
curl -fsSL https://api.github.com/repos/mnemon-dev/mnemon/releases/latest | grep '"tag_name"'
grep -q 'mnemon setup' container/entrypoint.sh && echo "Already wired" || echo "Wire it"
NanoClaw agent container entrypoint.
set -e
mnemon setup --target claude-code --yes --global >/dev/stderr 2>&1
cat > /tmp/input.json
exec bun run /app/src/index.ts < /tmp/input.json
cp .claude/skills/add-mnemon/mnemon-dockerfile.test.ts src/mnemon-dockerfile.test.ts
More from nanoclaw
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About this skill
What does the add-mnemon skill do?

Add persistent graph-based memory via mnemon. Agents recall past context before responding and remember insights after each turn.

How do I install it?

Run `npx skills add nanocoai/nanoclaw --skill add-mnemon --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From nanocoai/nanoclaw, a repository with 30,426 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going