Skill: grivn/mnemon (version 0.1.2)

--- name: mnemon description: "Persistent memory CLI for LLM agents. Store facts, recall past knowledge, link related memories, manage lifecycle." metadata: openclaw: emoji: "🧠" requires: bins: ["mnemon"] install: - id: "brew" kind: "brew" formula: "mnemon-dev/tap/mnemon" bins: ["mnemon"] label: "Install mnemon (Homebrew)" - id: "go" kind: "go" package: "github.com/mnemon-dev/mnemon@latest" bins: ["mnemon"] label: "Install mnemon (go install)" --- # mnemon ## Install & Configure ### 1. Install the binary **Homebrew** (macOS / Linux): ```bash brew install mnemon-dev/tap/mnemon ``` **Go install**: ```bash go install github.com/mnemon-dev/mnemon@latest ``` ### 2. Set up OpenClaw integration ```bash mnemon setup --target openclaw --yes ``` This single command deploys all components: - **Skill** → `~/.openclaw/skills/mnemon/SKILL.md` - **Hook** → `~/.openclaw/hooks/mnemon-prime/` (agent:bootstrap — injects behavioral guide) - **Plugin** → `~/.openclaw/extensions/mnemon/` (remind, nudge, compact hooks) - **Prompts** → `~/.mnemon/prompt/` (guide.md, skill.md) Restart the OpenClaw gateway to activate. ### 3. Customize (optional) Edit `~/.mnemon/prompt/guide.md` to tune recall/remember behavior. Plugin hooks are configured in `~/.openclaw/openclaw.json`: ```json { "plugins": { "entries": { "mnemon": { "enabled": true, "config": { "remind": true, "nudge": true, "compact": false } } } } } ``` | Hook | Default | Description | |------|---------|-------------| | `remind` | on | Recall relevant memories + remind agent on each message | | `nudge` | on | Suggest remember sub-agent after each reply | | `compact` | off | Save key insights before context compaction | ### 4. Uninstall ```bash mnemon setup --eject --target openclaw --yes ``` ## Workflow 1. **Remember**: `mnemon remember "<fact>" --cat <cat> --imp <1-5> --entities "e1,e2" --source agent` - Diff is built-in: duplicates skipped, conflicts auto-replaced. - Output includes `action` (added/updated/skipped), `semantic_candidates`, `causal_candidates`. 2. **Link** (evaluate candidates from step 1 — use judgment, not mechanical rules): - Review `causal_candidates`: does a genuine cause-effect relationship exist? `causal_signal` is regex-based and prone to false positives — only link if the memories are truly causally related. - Review `semantic_candidates`: are these memories meaningfully related? High `similarity` alone is not sufficient — skip candidates that share keywords but discuss unrelated topics. - Syntax: `mnemon link <id> <candidate> --type <causal|semantic> --weight <0-1> [--meta '<json>']` 3. **Recall**: `mnemon recall "<query>" --limit 10` ## Commands ```bash mnemon remember "<fact>" --cat <cat> --imp <1-5> --entities "e1,e2" --source agent mnemon link <id1> <id2> --type <type> --weight <0-1> [--meta '<json>'] mnemon recall "<query>" --limit 10 mnemon search "<query>" --limit 10 mnemon forget <id> mnemon related <id> --edge causal mnemon gc --threshold 0.4 mnemon gc --keep <id> mnemon status mnemon log mnemon store list mnemon store create <name> mnemon store set <name> mnemon store remove <name> ``` ## Guardrails - Use the `exec` tool to run mnemon commands. - Do not store secrets, passwords, or tokens. - Categories: `preference` · `decision` · `insight` · `fact` · `context` - Edge types: `temporal` · `semantic` · `causal` · `entity` - Max 8,000 chars per insight.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)