Total 30,768 skills, AI & Machine Learning has 4968 skills
Showing 12 of 4968 skills
Structured interactive learning assistant, used when users want to learn project-related knowledge, specific code files or underlying technologies. It records the learning process as persistent Markdown logs.
Detect and annotate hallucinations, unsupported claims, fabricated studies, and incorrect conclusions in text so that AI only cites verifiable, trustworthy content. Use this skill whenever the user asks you to fact-check, validate sources, check for hallucinations, or ensure that generated content is grounded in real evidence, even if they do not explicitly use the word "hallucination".
Enforces a 'Document-then-Execute' workflow. Use when an agent needs to run shell commands, execute tests, build projects, or perform any task that should favor established task runners (Makefile, npm run) and be logged to .cmds-by-agents/ for auditability.
Use this when you are exploring the codebase. It lets you ask the AI who wrote code questions about how things work and why they chose to build things the way they did. Think of it as asking the engineer who wrote the code for help understanding it.
Autonomous SDLC router. Takes a job, classifies complexity, executes the appropriate lev-* workflow (from trivial fix to full epic), and returns "done" with runnable instructions. One shot to full auto: spec/bd/poc/impl. Subagent returns completion artifact. Triggers: "sidequest", "side quest", "just do it", "autonomous", "one shot"
Use when an AI agent should run protocols or workflow tests against kairos-dev (KAIROS MCP in this repo's dev environment). Covers AI–MCP integration and workflow-test flows; MCP-only, reports/ output.
Use when the user needs to generate images, UI assets, icons, backgrounds, placeholders, or any visual content. Triggers on requests like "generate an image", "create a picture", "make an icon", "I need a visual for...".
Build AI-powered chat applications with TanStack AI and React. Use when working with @tanstack/ai, @tanstack/ai-react, @tanstack/ai-client, or any TanStack AI packages. Covers useChat hook, streaming, tools (server/client/hybrid), tool approval, structured outputs, multimodal content, adapters (OpenAI, Anthropic, Gemini, Ollama, Grok), agentic cycles, devtools, and type safety patterns. Triggers on AI chat UI, function calling, LLM integration, or streaming response tasks using TanStack AI.
This skill should be used when the user asks to "add resiliency to a skill", "make this skill more robust", "improve error handling", "add validation mechanisms", "create self-correcting behavior", or discusses determinism, robustness, error correction, or homeostatic patterns in Agent Skills. Applies biological resiliency principles from Michael Levin's work to Agent Skill design.
Design and enforce AI-friendly verification for a GRACE project. Use when modules need stronger automated tests, traceable logs, execution-trace checks, or verification that is robust enough for autonomous and multi-agent workflows.
This skill should be used when the user asks to "upscale an image", "increase image resolution", "make image bigger", "enlarge image", or "enhance image resolution". Requires Vertex AI credentials.
Crayfish Grid Hunter is an AI-powered grid trading assistant for Binance. It scans the market for optimal grid trading candidates, validates them with Smart Money signals and security audits, then generates dynamic grid ranges with risk management parameters. Use this skill when users ask about grid trading opportunities, coin screening, grid range analysis, or 'which coin is good for grid trading'.