Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/evanbong/memclawznpx agentmods add skills/evanbong/memclawz/skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/evanbong/memclawz/skill)<a href="https://agentmods.dev/skills/evanbong/memclawz/skill"><img src="https://agentmods.dev/badge/skills/evanbong/memclawz/skill/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/evanbong/memclawz/skill"><img src="https://agentmods.dev/badge/skills/evanbong/memclawz/skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.01496 |
| Opus 5.5 | $0.00000 | $0.00598 |
| Sonnet 5.5 | $0.00000 | $0.00299 |
| Haiku 4.5 | $0.00000 | $0.00150 |
Grade A, and why
skill scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -X POST http://localhost:4010/search \ This is a copy
91% identical to memclawz — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
memclawz — Three-Speed Memory Skill
Requires Python 3.10–3.13 (Python 3.14 not yet supported).
No API key required. Unlike other memory solutions that need OpenAI/Google/Voyage API keys, memclawz runs entirely locally using embedded models.
Install:
clawhub install yoniassia/memclawz
Give your OpenClaw agent structured working memory, fast vector search, and automatic compaction.
Why memclawz?
memclawz gives your agent a three-speed memory architecture: QMD (structured JSON) for instant working memory, Zvec (HNSW vector + BM25 hybrid) for fast semantic search, and MEMORY.md for curated long-term knowledge. Each layer is optimized for its access pattern, so your agent always uses the fastest path available.
- QMD — <1ms structured working memory (tasks, decisions, entities)
- Zvec — <10ms hybrid vector + keyword search over all indexed memory
- Built-in OpenClaw memory_search — ~1.7s (what you're replacing)
- Works offline, no API keys, no external calls
- Auto-imports your existing OpenClaw memory on first run — nothing to migrate manually
Quick Setup (One Command)
cd ~/.openclaw/workspace
git clone https://github.com/yoniassia/memclawz.git
cd memclawz && bash scripts/first-run.sh
This single command will:
- Install dependencies (zvec, numpy)
- Create QMD working memory
- Start the Zvec server
- Import ALL existing OpenClaw memory (SQLite + markdown files)
- Start the auto-indexing watcher
- Verify everything works
- Register as an OpenClaw skill
Re-sync history anytime: bash scripts/bootstrap-history.sh
Verify installation: python3 scripts/verify.py
What This Gives You
| Layer | Speed | What |
|---|---|---|
| QMD | <1ms | Structured JSON working memory — tasks, decisions, entities |
| Zvec | <10ms | HNSW vector + BM25 keyword hybrid search over all indexed memory |
| MEMORY.md | ~50ms | Curated long-term memory (OpenClaw built-in) |
Agent Protocol
On Session Start
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 182 lines · 0 tokens per session scan A b6b5c90f7dfa
skill is a skill published in the GitHub repository evanbong/memclawz (5 stars, last pushed 8mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,496 tokens. A static security scan graded it A with 1 finding (makes network calls). It is 91% identical to memclawz, differing in 8 lines, and is treated as a copy.
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