Total 50,539 skills, AI & Machine Learning has 8483 skills
Showing 12 of 8483 skills
This skill generates a structured chapter outline for intelligent textbooks by analyzing course descriptions, learning graphs, and concept dependencies. Use this skill after the learning graph has been created and before generating chapter content, to design an optimal chapter structure that respects concept dependencies and distributes content evenly across all of the chapter in a book.
Shell out to Cursor Agent CLI for headless IDE-aware code tasks. Supports multi-model routing (auto mode routes to Claude, Gemini, GPT). Requires Cursor Pro/Business subscription.
ElevenLabs text-to-speech with mac-style say UX.
Use when an existing agent needs Prefactor resources created via the Prefactor CLI before SDK instrumentation is added.
Social media intelligence monitoring for Novita. Use when systematically browsing X/Twitter accounts from personal following list (@Jax_Zhang_4R) to gather AI industry intelligence. Performs sequential account review with per-account record keeping (including original tweet links), followed by comprehensive summary. Always use @skills/twitterapi-cli for data retrieval.
Build vector retrieval with DashVector using the Python SDK. Use when creating collections, upserting docs, and running similarity search with filters in Claude Code/Codex.
Generate images with Model Studio DashScope SDK using Qwen Image generation models (qwen-image-max, qwen-image-plus-2026-01-09). Use when implementing or documenting image.generate requests/responses, mapping prompt/negative_prompt/size/seed/reference_image, or integrating image generation into the video-agent pipeline.
Model Context Protocol development expert. Use when creating MCP servers, clients, or tools that enable AI agents to interact with external systems, APIs, and development environments.
Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.
Coordinate complex work using a phase-gated, multi-agent engineering loop (audit → design → implement → review → validate → deliver). Use when you need to split a task into subsystems, run dual independent audits, reconcile findings into a confirmed issue list, delegate fixes in clusters, enforce dual-review PASS gates, and drive an end-to-end delivery. Prefer discovering and invoking other specialized skills when they can execute part of the work faster or more reliably.
Use after completing work sessions to analyze agent behavior patterns, prepare session handoffs for continuity, document completed work, identify blockers, or preserve context for the next session.