Total 56,830 skills, AI & Machine Learning has 9448 skills
Showing 12 of 9448 skills
Read production traces, identify what's failing, and build failure taxonomies using open coding and axial coding methodology. Use when debugging agent or pipeline quality, investigating "why are my outputs bad?", or before building any evaluator — error analysis must come first. Do NOT use when you already have identified failure modes and need evaluators (use build-evaluator) or datasets (use generate-synthetic-dataset).
Interactive lesson-level quiz for Claude Code tutorials. Tests understanding of a specific lesson (01-10) with 8-10 questions mixing conceptual and practical knowledge. Use before a lesson to pre-test, during to check progress, or after to verify mastery. Use when asked to "quiz me on hooks", "test my knowledge of lesson 3", "lesson quiz", "practice quiz for MCP", or "do I understand skills".
Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases.
Generate a complete set of multi-angle product shots — front, side, back, top-down, and 45-degree perspective — for comprehensive product visualization.
Script-First llms.txt generator. Uses a deterministic script to crawl the project structure, identify brand guides, and catalog content files. Provides a repo manifest for the agent to draft context-aware /llms.txt and /llms-full.txt files.
Connect ChatGPT / Codex subscription via OAuth device-code login (NOT BYOK)
Install and configure Oh My Hermes workflow layer for building, shipping, and operating apps with Hermes Agent
Hermes Labyrinth observability plugin for monitoring autonomous agent journeys, crossings, and execution traces
Resolves a PostHog experiment reference from natural language to a concrete experiment ID by browsing `experiment-list` (not feature-flag tools), with disambiguation when multiple experiments match. Use when the user names or quotes an experiment ("split test demo", "the File engagement boost experiment", "onboarding retention test", "landing page hero experiment", "pricing experiment"), describes it loosely ("the signup experiment", "my pricing test", "the one with the new checkout"), uses a relative reference ("latest", "most recent", "the one I created yesterday"), filters by status (running, draft, stopped, archived), or otherwise refers to an experiment by anything other than its concrete ID.
Run a safe, reviewable Aider CLI coding loop for local repositories: model setup, edit scope control, test-first prompting, commit hygiene, and fallback when agent edits drift. Use when the user wants pair-programming with Aider, not generic Git workflow or hosted PR operations.
Build typed LLM applications with PydanticAI: schema-constrained outputs, tool integration, validation, retries, and deterministic downstream handoffs. Use when users need reliable structured outputs instead of free-form text generation.
URDF robot description generation and default generation-time validation. Use when creating, editing, regenerating, inspecting, or debugging `.urdf` files, Python `gen_urdf()` sources, robot links, joints, limits, inertials, visual/collision geometry, mesh references, frame conventions, or generated robot-description artifacts. Use the SRDF skill for MoveIt2 semantic groups and IK/path-planning semantics; use the render skill for local MoveIt2 server controls; use the CAD skill for STEP/STL/3MF/DXF/GLB outputs.