Total 50,553 skills, AI & Machine Learning has 8484 skills
Showing 12 of 8484 skills
Parallel Agent Orchestration
System health check (MOT) for skills, agents, hooks, and memory
Use when about to ask the user a factual question, propose a solution, diagnose an error, or choose between approaches. Triggers on: 'Do you have X installed?', 'What version?', 'Is X configured?', 'We should...', 'The fix is...', 'Options: 1...', 'Based on my understanding...', 'I believe X supports...'. Before deciding anything, spin up parallel subagents to WebSearch for current docs, community solutions, framework best practices, and GitHub issues. Your memory is stale — verify everything.
Designs album concepts, tracklist architecture, and thematic planning through 7 structured phases. Use when planning a new album or reworking an existing album concept.
Use when substantive documents (reviews, analyses, synthesis documents) need adversarial review to strengthen arguments, identify weak points, and challenge assumptions before editorial polish (mandatory for Writer → Devil's Advocate pairing protocol)
Generate AI videos using Kling video generation models. Use when you need to: (1) create videos from text prompts, (2) animate images into videos, (3) transform existing videos with AI, or (4) create AI avatar videos with speech.
Stops execution and fixes root cause when commands, builds, scripts, or tools fail unexpectedly. Triggers on workaround language: 'directly', 'instead', 'alternatively', 'skip', 'fall back', 'work around', 'isn't working', 'broken', 'manually'. Activates on any unexpected non-zero exit code or process failure.
Scans lyrics for pronunciation risks and prevents Suno mispronunciations. Use when writing lyrics with proper nouns, technical terms, homographs, or non-English words.
Use Collabute MCP for organization-specific context retrieval and proposal-safe actions. Trigger when users ask about meetings, memory, Linear, Slack, or Vercel data from their Collabute workspace, or ask to create tasks from meeting context.
Frames coding-agent work sessions with explicit intent capture and drift monitoring. Use when a session transitions from planning/Q&A to implementation for coding tasks, refactors, feature builds, bug fixes, or other multi-step execution where scope drift is a risk.
Creates implementation-only tracker subtasks from `technical-details` using handoff-first context loading, lazy artifact reads, and compact JSON handoff output.
N coordinated agents on shared task list (compatibility facade over team)