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Found 38 Skills
Security audit and vulnerability scanning for AI agent skills before installation. Detects prompt injection in SKILL.md files, dangerous code patterns (eval, exec, subprocess), network exfiltration, credential harvesting, dependency supply chain risks, file system boundary violations, and obfuscation. Produces PASS/WARN/FAIL verdicts with remediation guidance. Use when evaluating untrusted skills, pre-install security gates, or auditing skill repositories.
AI/LLM application security testing — prompt injection, jailbreaking, data exfiltration, and insecure output handling per OWASP LLM Top 10.
Debug and harden production LLM prompts — handle prompt injection, output format drift, instruction forgetting in long contexts, and cross-model portability issues. Use this skill when the user ships an LLM-powered feature to production and needs to diagnose why outputs are inconsistent, unsafe, or regressed after model updates — NOT for basic 'write a better prompt' questions.
Review, audit, and harden AI skills for security risks including prompt injection, hidden instructions, tool misuse, data exfiltration, and malicious payloads; use when analyzing SKILL.md, scripts, references, or assets for vulnerabilities and when producing remediation guidance.
Prompt design patterns for LLMs including few-shot, chain-of-thought, structured output, and injection defense. Use when crafting prompts, optimizing LLM outputs, or building prompt-based features.
Security auditor for Claude Code skills and agent definitions. Scans a skill or agent directory for prompt injection, data exfiltration, privilege escalation, memory poisoning, obfuscation, malicious persistence, and 12 other threat categories (18 total). Returns a graded verdict (OK / WARNING / CRITICAL) with detailed findings. Use this skill whenever you need to audit, review, or validate the safety of a skill, an agent definition, a system prompt, or any set of instruction files before installing or trusting them. Also use it when the user mentions security scanning, threat detection, prompt injection checking, or wants to verify that a skill is safe. Triggers on: /maton, "audit this skill", "is this skill safe", "check for injection", "scan for threats", "review this agent", "security check".
Scan agent skills for security issues. Use when asked to "scan a skill", "audit a skill", "review skill security", "check skill for injection", "validate SKILL.md", or assess whether an agent skill is safe to install. Checks for prompt injection, malicious scripts, excessive permissions, secret exposure, and supply chain risks.
Use this skill whenever Claude needs to fetch, read, extract, or analyze content from a web URL. Converts web pages into clean, token-efficient markdown using the markdown.new service instead of fetching raw HTML. Trigger when the user provides a URL and wants its content summarized, quoted, analyzed, compared, extracted, or processed. Also trigger when Claude needs to read documentation, blog posts, articles, wikis, release notes, changelogs, or any web-hosted text content. Even if the user just pastes a URL with no instruction, use this skill. Do NOT use for binary files, authenticated pages, or API endpoints returning JSON/XML.
Use this skill when auditing AI agent skills for security vulnerabilities, prompt injection, permission abuse, supply chain risks, or structural quality. Triggers on skill review, security audit, skill safety check, prompt injection detection, skill trust verification, skill quality gate, and any task requiring security analysis of AI agent skill files.
Semantic security scanner for OpenClaw skills. Detects prompt injection, data exfiltration, and hidden instructions that traditional code scanners miss. Use when user asks to scan skills, check skill safety, or run a security audit.
Comprehensive security auditor for AI agent skills, prompts, and instructions. Checks for typosquatting, dangerous permissions, prompt injection, supply chain risks, and data exfiltration patterns — before you use any agent or skill.
Comprehensive guide to why and how AI agents should use email. Use when evaluating whether an agent needs email, comparing email infrastructure options (AgentMail vs Gmail API vs Resend vs SendGrid vs SES), understanding security risks like prompt injection via email and OAuth credential exposure, or exploring common agent email use cases such as customer support agents, sales outreach, verification flows, and browser automation.