Total 31,643 skills, AI & Machine Learning has 5103 skills
Showing 12 of 5103 skills
Query fan-out coverage for AI visibility. Covers semantic variation analysis and sub-question targeting.
Fix, configure, tune, or troubleshoot OpenClaw. Use for config changes, security fixes, performance tuning, doctor --fix, or when openclaw-doctor flags issues that need remediation.
Semantic and multi-modal search across documents using LanceDB vector embeddings. Use when searching knowledge bases, finding information semantically, ingesting documents for RAG, or performing vector similarity search. Triggers on "search documents", "semantic search", "find in knowledge base", "vector search", "index documents", "LanceDB", or RAG/embedding operations.
Analyze text and images for harmful content using Azure AI Content Safety (@azure-rest/ai-content-safety). Use when moderating user-generated content, detecting hate speech, violence, sexual conten...
Four common skill archetypes with structure templates - CLI reference, methodology, safety/security, and orchestration. Use when creating new skills to select appropriate structure.
Add descriptions for new models from the HuggingFace router to chat-ui configuration. Use when new models are released on the router and need descriptions added to prod.yaml and dev.yaml. Triggers on requests like "add new model descriptions", "update models from router", "sync models", or when explicitly invoking /add-model-descriptions.
Comprehensive LLM audit. Model currency, prompt quality, evals, observability, CI/CD. Ensures all LLM-powered features follow best practices and are properly instrumented. Auto-invoke when: model names/versions mentioned, AI provider config, prompt changes, .env with AI keys, aiProviders.ts or prompts.ts modified, AI-related PRs. CRITICAL: Training data lags months. ALWAYS web search before LLM decisions.
Run MassGen experiments and analyze logs using automation mode, logfire tracing, and SQL queries. Use this skill for performance analysis, debugging agent behavior, evaluating coordination patterns, and improving the logging structure, or whenever an ANALYSIS_REPORT.md is needed in a log directory.
Technical mechanics for autonomous AI coding loops
Creates comprehensive implementation plans with exact file paths, complete code examples, and verification steps for engineers with zero codebase context.
Helps you create and refine new Gravito Skills. Trigger this when asked to add a new skill to the ecosystem.
Mandatory orchestrator protocol - establishes ORCHESTRATOR principle (dispatch agents, don't operate directly) and skill discovery workflow for every conversation.