OpenClaw Master Skills is a curated, regularly updated collection of skills that extends an AI personal assistant platform with capabilities such as research, browser automation, presentation creation, and prompt work. It is intended for people using OpenClaw or MyClaw.ai to give their agents additional tasks and workflows. The catalogue contains many skills and agents from this collection.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add LeoYeAI/openclaw-master-skills --skill analyzegit clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skillsWrote 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/leoyeai/openclaw-master-skills/analyze)<a href="https://agentmods.dev/skills/leoyeai/openclaw-master-skills/analyze"><img src="https://agentmods.dev/badge/skills/leoyeai/openclaw-master-skills/analyze/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/leoyeai/openclaw-master-skills/analyze"><img src="https://agentmods.dev/badge/skills/leoyeai/openclaw-master-skills/analyze.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 44 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 47 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00056 | $0.01098 |
| Opus 5 | $0.00028 | $0.00549 |
| Sonnet 5 | $0.00011 | $0.00220 |
| Haiku 4.5 | $0.00006 | $0.00110 |
Grade A, and why
agent-bom-analyze scanned grade A with 0 findings 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 9d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- agent-bom-analyze — 95% identical, 17 lines differ
How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
agent-bom-analyze — Blast Radius & Attack Path Analysis
Analyzes blast radius, attack paths, and the threat landscape across your AI infrastructure. Maps lateral movement risks, identifies high-impact CVEs, and visualizes agent context graphs.
Install
pipx install agent-bom
agent-bom agents --verbose # blast radius detail for each agent
agent-bom graph # generate context graph
When to Use
- "blast radius" / "what's the blast radius"
- "threat intel" / "threat intelligence"
- "risk score" / "risk scoring"
- "attack path" / "attack paths"
- "lateral movement"
- "context graph" / "agent graph"
- "who can reach what"
Commands
# Blast radius detail (verbose)
agent-bom agents --verbose
# Generate context graph
agent-bom graph
Tools
| Tool | Description |
|---|---|
blast_radius |
Map CVE impact chain across agents, servers, and credentials |
context_graph |
Agent context graph with lateral movement analysis |
analytics_query |
Query vulnerability trends, posture history, and risk scores |
Examples
# Map blast radius of a specific CVE
blast_radius(cve_id="CVE-2024-21538")
# Build full context graph
context_graph()
# Query top CVEs by blast radius impact
analytics_query(query="top_blast_radius", days=30)
Example blast radius output:
CVE-2024-21538 — CRITICAL (CVSS 9.8, EPSS 0.94)
Blast Radius: 4 agents affected
filesystem [direct] langchain 0.1.0 → CVE-2024-21538
└─ github [indirect] shares filesystem credential scope
└─ slack [indirect] accessible via filesystem tool call
postgres [direct] langchain 0.1.0 → CVE-2024-21538
Recommended: Update langchain to ≥ 0.1.17
Guardrails
- Analysis is read-only — no files are modified.
- Only public CVE IDs are sent externally (to EPSS and vulnerability databases).
- No internal config data, credentials, or agent details leave the machine.
- Present blast radius findings clearly and ask the user whether to generate a remediation plan when CRITICAL CVEs are found.
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.
- 9d ago First seen · 131 lines · 56 tokens per session scan A e9b0363362bc
agent-bom-analyze is a skill published in the GitHub repository LeoYeAI/openclaw-master-skills (2,141 stars, last pushed 1mo ago), licensed MIT. It adds 56 tokens to every session and 1,098 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
comfyui-skill-openclaw
Run registered ComfyUI workflows through the fast comfyui-skill CLI, and use the official local Comfy MCP for live template, node, model, validation, and orchestration capabilities. Use this Skill when: (1) The user requests to "generate an image", "draw a picture", or "execute a ComfyUI workflow". (2) The user has…
openclaw-auto-dream
Cognitive memory architecture for OpenClaw agents — periodic dream cycles that consolidate daily logs into structured long-term memory with importance scoring, insights, and push notifications. Use when: user asks for 'auto memory', 'dream', 'auto-dream', 'memory consolidation', 'memory dashboard'. Powered by…
openclaw-ultra-scraping
Powerful web scraping, crawling, and data extraction with stealth anti-bot bypass. Bypasses anti-bot systems (Cloudflare Turnstile, CAPTCHAs) out of the box. Use when: (1) scraping websites that block normal requests, (2) extracting structured data from web pages, (3) crawling multiple pages with concurrency, (4)…
myclaw-backup
Backup and restore all OpenClaw configuration, agent memory, skills, and workspace data. Part of the MyClaw.ai (https://myclaw.ai) open skills ecosystem — the AI personal assistant platform that gives every user a full server with complete code control. Use when the user wants to create a snapshot of their OpenClaw…
agentsec
Audit AI agent skills for security vulnerabilities. Use when scanning installed skills against the OWASP Agentic Skills Top 10, checking skills before running them, gating CI/CD on skill safety, or generating audit reports (text, JSON, SARIF, HTML) for stakeholders.
create-teammate
Distill a teammate into an AI Skill. Auto-collect Slack/Teams/GitHub data, generate Work Skill + 5-layer Persona, with continuous evolution. Use when: user wants to capture a colleague's knowledge before they leave, create an AI version of a teammate, distill tribal knowledge into a reusable skill, or says…