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Found 30 Skills
Security patterns for LLM integrations including prompt injection defense and hallucination prevention. Use when implementing context separation, validating LLM outputs, or protecting against prompt injection attacks.
OWASP Top 10 for LLM Applications - prevention, detection, and remediation for LLM and GenAI security. Use when building or reviewing LLM apps - prompt injection, information disclosure, training/supply chain, poisoning, output handling, excessive agency, system prompt leakage, vectors/embeddings, misinformation, unbounded consumption.
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.
AI/LLM application security testing — prompt injection, jailbreaking, data exfiltration, and insecure output handling per OWASP LLM Top 10.
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.
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.