Total 51,079 skills, AI & Machine Learning has 8556 skills
Showing 12 of 8556 skills
Generate anime-style video prompts for Seedance 2.0 (Higgsfield). Use this when users want anime, Japanese animation style, shonen manga action, seinen manga drama, magical girl, mecha, isekai, slice-of-life anime, or any Japanese animation aesthetics. Trigger conditions: anime, Japanese animation, shonen manga, seinen manga, manga-style video, anime fight, anime opening, anime ending, cherry blossoms, chibi, cute style, mecha, isekai, or any anime-style request. Even phrases like "make it look like anime" or "Japanese cartoon style".
This skill should be used when a developer wants to autonomously execute all tasks under a fully-specified Epic or Feature — for example "go", "start building", "implement everything", "run the loop", "execute the feature", "build it all", "kick it off". Requires that the Epic/Feature/Task tree is fully written before starting. Chains implement → verify → PR for every task in dependency order, with targeted human-in-the-loop gates for contradictions and ambiguities.
Knowledge Base RAG implements the complete Retrieval-Augmented Generation pipeline: document ingestion, intelligent chunking, embedding generation, vector store indexing, semantic retrieval, and grounded response generation.
Investigate Bedrock AgentCore runtime sessions via CloudWatch Logs Insights — resolve session/trace IDs, query OTEL spans, filter noise, build timelines. Use when debugging AgentCore agent sessions, tracing tool calls, or analyzing latency.
Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus
Attach judges to AI Config variations for automatic LLM-as-a-judge evaluation. Create custom judges, configure sampling rates, and monitor quality scores.
Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, alerts with webhooks, HF Space syncing, and JSON output for automation.
Complete reference for Runway's public API: models, endpoints, costs, limits, and types
Deploys agent skill collections from any GitHub repository with a /skills folder to one or more distribution surfaces: GitHub releases, Claude Code marketplace, VS Code plugin marketplace, and Copilot CLI plugin marketplace. Handles pre-flight validation, conventional commit analysis, version bumping across surface configs, and surface-specific publishing with dry-run support. Use when releasing, publishing, or deploying a skills collection to any supported marketplace or creating a GitHub release for a skills repository. Don't use for deploying non-skill packages, npm modules, Docker images, or Azure resources.
Invoke MassGen's multi-agent system. Use when the user wants multiple AI agents on a task: writing, code, review, planning, specs, research, design, or any task where parallel iteration beats working alone.
Interactive onboarding tour for the context-matic MCP server. Walks the user through what the server does, shows all available APIs, lets them pick one to explore, explains it in their project language, demonstrates model_search and endpoint_search live, and ends with a menu of things the user can ask the agent to do. USE FOR: first-time setup; "what can this MCP do?"; "show me the available APIs"; "onboard me"; "how do I use the context-matic server"; "give me a tour". DO NOT USE FOR: actually integrating an API end-to-end (use integrate-context-matic instead).
Retrieve the status of the last diagnosis to continue using it. Use in conjunction with dbs-save. Trigger methods: /dbs-restore, /continue, "continue from last time", "previous conclusion", "where did we leave off in the last diagnosis" Restore the most recent diagnosis snapshot saved by dbs-save. Trigger: /dbs-restore, "continue from last time", "where did we leave off"