4.8k Downloads
Overview
Local-first, structured long-term memory system and OpenClaw hook pack that builds a typed knowledge graph from markdown, manages agent context across sessions (wake/sleep/checkpoint/handoff), and provides search, semantic retrieval, and session-transcript repair tools via a CLI.
Key Advantages
1.Rich feature set for agent memory: typed memories (decisions, lessons, people, projects, etc.), inbox capture, context profiles, handoffs, checkpoints, and recap flows designed specifically for OpenCl
2.Graph-aware context retrieval combining semantic search and knowledge-graph neighbors built from wiki-links, tags, and frontmatter.
3.Deep OpenClaw integration via lifecycle hooks (startup, heartbeat, new command, session start, memory flush, cron weekly) plus a dedicated compatibility diagnostic command.
4.Local-first, auditable design: data stored as markdown in a user-controlled vault, hooks and handler source shipped in the bundle (SKILL.md, HOOK.md, handler.js) for inspection before enabling.
5.Resilience to "context death" and transcript issues via wake/sleep/checkpoint/recover flows and a focused `repair-session` utility with dry-run and automatic backups for OpenClaw sessions.
Integration
Use Cases
- Running OpenClaw agents with durable, structured memory across many sessions, including clear summaries, next steps, and blockers (wake/sleep/handoff flows).
- Maintaining a personal or team knowledge base for agents using markdown files, wiki-links, and tags, while enabling agents to retrieve context via graph-aware search.
- Diagnosing and repairing broken OpenClaw session transcripts (e.g., orphaned tool_result blocks or invalid tool_use chains) with `repair-session` in CI or during incident response.
- Supporting specialized agent behaviors via context profiles (planning, incident, handoff, default) that tailor what context is fed into LLM prompts.
- Improving agent reliability in long-running or multi-step tasks by encouraging regular checkpoints and health checks (`checkpoint`, `doctor`, `compat --strict`).
Evaluation Scores
8.4
/ 10
Reliability
8.6
Functionality
9.1
Usability
7.7
Safety
7.9
Performance
8.4
Compatibility
8.7
Based on 1 evaluation · Latest: 3/19/2026
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Evaluation History (1)
8.4/103/19/2026▼
OS: linux-arm64LLM: anthropic/claude-haiku-4.5
**Judgement:** ClawVault appears to be a mature, well-engineered memory system for OpenClaw agents, suitable for serious and even production-like use by technically comfortable users who want durable, structured agent memory and are willing to manage a CLI- and hook-based workflow.
**What it does well**
- Provides a comprehensive memory layer: structured markdown vault, typed memories (decisions, lessons, relationships, projects, etc.), inbox capture, handoffs, wake/sleep/checkpoint/recover, and graph-aware context retrieval.
- Integrates tightly with OpenClaw via hooks and dedicated diagnostics (`clawvault compat`, `doctor`), plus a well-defined folder structure and context profiles tuned to common agent situations (planning, incident, handoff).
- Uses a local-first, auditable design: all memory is on the local filesystem; the skill bundle includes SKILL.md, HOOK.md, and the hook handler so users can inspect behavior before enabling.
- Offers operational tooling for robustness, including a `repair-session` command to fix known transcript pathologies and automatic backups/dry-run modes.
**Key risks / caveats**
- **High-privilege filesystem access:** By design, it reads/writes extensively in the vault directory and modifies OpenClaw session transcripts. Misconfiguration or bugs could corrupt data, though backups and dry-runs mitigate this.
- **External LLM dependency for `observe`:** The optional observation-compression flow calls Gemini (via GEMINI_API_KEY). This can leak transcript content to a third-party LLM; it must be disabled/avoided for strictly air-gapped or highly regulated environments.
- **Operational complexity:** Setup requires npm, qmd, OpenClaw CLI, hook installation/enabling, and environment configuration. It’s best suited to users comfortable with CLI tools, inspecting JS source, and managing their agent runtime.
**Recommended scenarios**
- Teams or power users running OpenClaw agents that need long-lived, inspectable memory and stable cross-session continuity.
- Workflows where agents must track projects, people, decisions, and lessons over time with clear handoffs and recovery from context loss.
- Environments where local, markdown-based storage is preferred and users are willing to review hooks and manage security posture around the optional Gemini integration.
**Less ideal for**
- Users seeking a minimal, zero-setup memory layer or those uncomfortable enabling filesystem-writing hooks.
- Strictly regulated or air-gapped deployments unless the `observe`/Gemini integration is disabled and the hook’s behavior is carefully audited.
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