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Found 270 Skills
End-to-end interactive workflow — pick a product, then either run existing tasks and environments (Path A) or set up new ones from docs, suggested tasks, credentials, and templates (Path B). Builds the experiment, attaches signals, and optionally triggers the first iteration. Trigger when users say: "set up an experiment", "create an experiment", "I want to run an experiment", "run my tasks", "setup experiment", "new experiment", "configure an experiment", or "experiment setup".
Transform prompts into structured TCRO format with phase-specific clarification. Automatically invoked by /ai-eng/research, /ai-eng/plan, /ai-eng/work, and /ai-eng/specify commands. Use when refining vague prompts, structuring requirements, or enhancing user input quality before execution.
Background Agent Pings
AI prompt orchestration CLI using reusable Patterns. Use for YouTube summarization, document analysis, content extraction, code explanation, writing assistance, and any AI task via stdin/stdout piping across 20+ providers.
Comprehensive guide for skill development based on Anthropic's official best practices - use for complex skills requiring detailed structure
Multi-agent consensus voting with domain-weighted expertise for critical decisions requiring structured validation
Create and edit videos using Google's Veo 2 and Veo 3 models. Supports Text-to-Video, Image-to-Video, Inpainting, and Advanced Controls.
Execute Groq secondary workflow: Core Workflow B. Use when implementing secondary use case, or complementing primary workflow. Trigger with phrases like "groq secondary workflow", "secondary task with groq".
Updates model references across all skill files when new Claude models are released. Use when Anthropic releases new Claude models to keep skills current.
Iteratively auto-optimize a prompt until no issues remain. Uses prompt-reviewer in a loop, asks user for ambiguities, applies fixes via prompt-engineering skill. Runs until converged.
Workflow 1 adaptation for robotics and embodied AI. Orchestrates robotics-aware literature survey, idea generation, novelty check, and critical review to go from a broad robotics direction to benchmark-grounded, simulation-first ideas. Use when user says "robotics idea discovery", "机器人找idea", "embodied AI idea", "机器人方向探索", "sim2real 选题", or wants ideas for manipulation, locomotion, navigation, drones, humanoids, or general robot learning.
Use this skill when retrieving Jira tickets, analyzing requirements, updating ticket status, adding comments, or transitioning issues. Provides Jira API patterns via MCP or direct REST calls.