Loading...
Loading...
Found 1,197 Skills
Interact with X (Twitter) API v2. Post tweets, search, engage, moderate, and analyze — all from your AI agent. Full 31-command skill for Twitter/X automation.
Meta-skill for understanding and customizing Mindfold Trellis - the AI workflow system for Claude Code and Cursor. This skill documents the ORIGINAL Trellis system design. When users customize their Trellis installation, modifications should be recorded in a project-local `trellis-local` skill, NOT in this meta-skill. Use this skill when: (1) understanding Trellis architecture, (2) customizing Trellis workflows, (3) adding commands/agents/hooks, (4) troubleshooting issues, or (5) adapting Trellis to specific projects.
Production-grade Next.js chatbot builder. Covers tool calling with human-in-the-loop (HITL) approval, PostgreSQL session persistence, GDPR consent gating, SQL-first search, per-tool UI rendering, message feedback, and follow-up suggestions. Use when building chat apps, conversational AI interfaces, customer support bots, or any chatbot needing database-backed sessions, tool approval workflows, consent gating, or custom tool output components. Reference implementation: fair-helpdesk project.
AI-powered OSINT agent with interactive REPL, MCP server, and CLI for email/username/domain/IP/phone investigation using 11 integrated tools
Activates when the user asks about Agent Skills, wants to find reusable AI capabilities, needs to install skills, or mentions skills for Claude. Use for discovering, retrieving, and installing skills.
Discover, connect and use over 100K+ MCP tools and skills from the Smithery marketplace.
Slack automation CLI for AI agents. Use when: - Reading a Slack message or thread (given a URL or channel+ts) - Downloading Slack attachments (snippets, images, files) to local paths - Searching Slack messages or files - Sending a reply or adding/removing a reaction - Fetching a Slack canvas as markdown - Looking up Slack users Triggers: "slack message", "slack thread", "slack URL", "slack link", "read slack", "reply on slack", "search slack"
Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.
Amazon Bedrock AgentCore Evaluations for testing and monitoring AI agent quality. 13 built-in evaluators plus custom LLM-as-Judge patterns. Use when testing agents, monitoring production quality, setting up alerts, or validating agent behavior.
Expert guidance for creating Claude Code skills and slash commands. Use when working with SKILL.md files, authoring new skills, improving existing skills, creating slash commands, or understanding skill structure and best practices.
Use when asked to detect silent failures/weak error handling or explicitly asked to run the silent-failure-hunter subagent.
Project setup. Explore the codebase, ask about strategy and aims, write persistent context to AGENTS.md. Run when starting or when aims shift.