What does this skill do, and when should you use it?
ClawSec for NanoClaw monitors security advisories for NanoClaw skills and dependencies used by WhatsApp bots. Its MCP tools check prospective and installed skills, expose exploitability context, and support package signature, file-integrity, baseline, and audit-log verification. It is a fit for teams that need supply-chain and advisory monitoring around NanoClaw. It is explicitly not intended for code review, performance troubleshooting, or general debugging.
It calls clawsec_check_skill_safety for a prospective skill, clawsec_check_advisories for an installed-skill audit, and clawsec_list_advisories to filter the advisory feed by severity, type, or exploitability. It also exposes clawsec_verify_skill_package, clawsec_refresh_cache, clawsec_check_integrity, clawsec_approve_change, clawsec_integrity_status, and clawsec_verify_audit. The skill consumes the signed feed at https://clawsec.prompt.security/advisories/feed.json and uses /workspace/project/data/clawsec-advisory-cache.json as its stated cache location.
- A NanoClaw administrator checks a requested skill before installing it.
- A bot maintainer answers whether the installed skills have known vulnerabilities.
- A security operator investigates suspicious skill behavior using advisory and exploitability context.
- An operations team runs recurring audits and alerts on critical or highly exploitable matches.
- A standalone installer verifies the release manifest, signature, public-key fingerprint, archive, and package files before extraction.
How do you install this skill?
- Before installation, verify the NanoClaw and Node.js versions, host paths, and every MCP/IPC integration point; the documented .js imports may require a build step for the provided .ts sources.
- Do not treat a valid signature or absence of advisories as proof of complete safety; compromised signing keys, zero-days, malicious signed packages, and post-check modifications remain possible.
- Use the default automatic restoration cautiously in production, preserving quarantine, patch, and audit artifacts; ensure stale cache data is not presented as a current security conclusion.
- Version-range matching is marked TODO and should be checked before relying on version-specific advisory results.
- The core feed depends on an overseas domain; verify mainland-China connectivity and prepare a trusted mirror or explicit offline policy.
- Shell / CLI
- Network access
- Local filesystem
- MCP Server
Node.js/npmcurlOpenSSLjq
Install it with the Vercel Skills CLI: npx skills add prompt-security/clawsec --skill clawsec-nanoclaw -a openclaw -y. The supplied material does not include the full manual NanoClaw deployment procedure; for standalone releases, follow the provided manifest-verification procedure before extracting or installing the archive.
tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/prompt-security/clawsec.git "$tmp"
mkdir -p ~/.claude/skills
cp -R "$tmp/skills/clawsec-nanoclaw" ~/.claude/skills/
rm -rf "$tmp"Generated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.
How do you use this skill?
Once installed, send your agent any of these to trigger it:
- Are my skills secure?
- Check my NanoClaw skills for security advisories.
Before installing a skill, call clawsec_check_skill_safety({skillName: "new-skill", skillVersion: "1.0.0"}). To audit installed skills, call clawsec_check_advisories({installRoot: "/home/node/.claude/skills"}) and prioritize matches with critical severity or high exploitability. Example user triggers include “Are my skills secure?” and “Check my NanoClaw skills for security advisories.”
What are this skill's strengths and limitations?
- Covers pre-install checks, installed-skill audits, and advisory browsing.
- Combines severity with exploitability context for triage.
- Includes package verification and file-integrity-related operations.
- Targets NanoClaw directly and provides a daily scheduled-check example.
- Requires network access and an MCP-capable runtime.
- The supplied source omits the detailed INSTALL.md and docs content, so deployment configuration requires consulting the repository.
- It does not cover code review, performance issues, or general debugging.
- The stated default audit and cache paths may need adjustment for a specific environment.
How does this skill compare with similar options?
Side by side with related skills; every score comes from the same FSRS standard.
| Skill | FS score | Stars | Last updated | License |
|---|---|---|---|---|
| NanoClaw Security Sentinel this page | 44 · Not recommended | ★ 1.1k | 14d ago | AGPL-3.0 |
| Prism Scanner — AI Agent Skill Security Scanner | 55 · Use with care | ★ 27 | 6mo ago | Apache-2.0 |
| n8n MCP Tools Expert | 45 · Not recommended | ★ 6.4k | 18d ago | MIT |
| NanoClaw Traffic Guardian | 48 · Use with care | ★ 1.1k | 14d ago | AGPL-3.0 |
| Picoclaw Security Guardian | 55 · Use with care | ★ 1.1k | 14d ago | AGPL-3.0 |
How did FollowSkills review this skill?
The evidence shows host-side IPC, Ed25519 verification, a pinned public key, bounded paths, symlink rejection, atomic cache writes, container isolation for baselines, and quarantine/restore handling; remote-feed data flow is disclosed. Points are deducted because automatic restoration is enabled by default and changes critical files, user confirmation is not enforced, stale cache use is possible, and publisher identity plus the key-establishment path remain incomplete.
The documentation covers installation, integration, troubleshooting, and failure logging; the code includes timeouts, fail-closed signature checks, atomic writes, and refresh de-duplication. Points are deducted because this is a static review capped at 10, version-range matching is still marked TODO despite the changelog claiming support, and several import, path, and runtime-environment assumptions are not reproducible from the selected evidence.
The audience, NanoClaw use cases, triggers, and non-fit cases are mostly clear, with several MCP tools. Points are deducted for no Chinese-language support or localized output and reliance on a single overseas HTTPS advisory service; mainland-China reachability and offline behavior are not sufficiently bounded despite cache fallback documentation.
The directory provides layered installation, configuration, examples, FAQs, troubleshooting, limitations, uninstall instructions, AGPL-3.0-or-later licensing, versioning, a changelog, and support/issue channels. Points are deducted because maintenance ownership is broad rather than operationally explicit, updates depend on external services, and some documented versions, paths, and implementation details conflict.
The claimed functions can plausibly perform advisory checks, package verification, and file-integrity monitoring, with directly usable MCP examples. Points are deducted because static evidence cannot establish end-to-end operation; version matching remains unfinished, deployment requires host integration and an external feed, and outputs plus automatic restoration still require human review.
Committed implementation code, type definitions, a pinned key, policy, changelog, and concrete interface examples provide limited auditability. Points are deducted because no execution occurred, the selected evidence lacks verifiable CI and comprehensive key-path tests, and claims such as “zero false positives” and “production-ready” are unsupported.
Open a dimension to read why it scored that way
Evidence confidence：Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.
See the full review method →