Total 53,877 skills, AI & Machine Learning has 8964 skills
Showing 12 of 8964 skills
JingSwap STX↔sBTC cycle monitor and participation agent. Reads live cycle state and prices directly from the Stacks contract via Hiro API and Pyth oracle — no API key required. Outputs PARTICIPATE / MONITOR / WAIT_FOR_DEPOSIT_PHASE / NO_SBTC_AVAILABLE with oracle-vs-DEX discount analysis.
Use these skills to set up and optimize production-ready vector workloads by simply expressing your intent and performance requirements.
Use the unified Opper SDKs (`opperai` package for both Python and TypeScript, with built-in agent support) for AI task completion, structured output with Pydantic / Zod / JSON Schema, knowledge base semantic search, streaming, tracing, tool use, and multi-agent composition. Use this skill whenever the user is writing Python or TypeScript code that imports `opperai`, builds an Opper agent, or asks how to do anything Opper-related in code — even if they don't explicitly name the SDK. Both languages live in one repo with parallel numbered examples; agents are part of the SDK, not a separate package.
Estratega de Inteligencia de Dominio de Andru.ia. Analiza el nicho específico de un proyecto para inyectar conocimientos, regulaciones y estándares únicos del sector. Actívalo tras definir el nicho.
Use this skill when the user types "/notes" or "@notes" with phrases like "save this", "document this", "file this under <project/client>", "extract decisions", "extract action items", or "update notes from this discussion". The skill spawns the notes-librarian subagent to extract durable knowledge and file it into the right Docmost page using the existing workspace structure. Falls back to a configured inbox page when confidence is low.
Score and compare images using vision LLMs as judges. YAML-defined criteria presets for 11 use cases (text-to-image, photorealism, document OCR, charts, UI, portrait, product, scientific, invoice, alt-text, artistic style). Supports OpenAI, Anthropic, Gemini, Mistral, and OpenRouter as judge providers. Keys auto-decrypted via SOPS + age.
Compiles any research input — PDF papers, GitHub repositories, experiment logs, code directories, or raw notes — into a complete Agent-Native Research Artifact (ARA) with cognitive layer (claims, concepts, heuristics), physical layer (configs, code stubs), exploration graph, and grounded evidence. Use when ingesting a paper or codebase into a structured, machine-executable knowledge package, building an ARA from scratch, or converting research outputs into a falsifiable, agent-traversable form.
Run an autonomous /loop iteration -- check progress, work on next task, schedule next wake
Synthesize research findings from memory into structured reports with evidence grading, contradiction resolution, and actionable recommendations
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "multi-agent", "agent swarm", "coordinator agent", "worker agent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", "agents that communicate", "parallel agents", or needs guidance on agent structure, system prompts, triggering conditions, subagent orchestration, or multi-agent swarm development for Claude Code.
Audio generation skill — jingles, beds, voiceover, and sound effects. Routes music requests to Suno V5 / Udio / Lyria, speech to MiniMax TTS / FishAudio / ElevenLabs V3, and SFX to ElevenLabs SFX or AudioCraft. Output is one MP3/WAV file saved to the project folder.
Reusable better-chatbot patterns for custom deployments. Use for server action validators, tool abstraction, multi-AI providers, or encountering auth validation, FormData parsing, workflow execution errors.