Loading...
Loading...
Found 173 Skills
Initialize the memory system in the current directory, generating CLAUDE.md (optional AGENT.md for Cursor), MEMORY.md, and the memory/ directory. Triggered when the user says "initialize memory", "set up memory", "memory init", or "/memory-init".
Create, query, update, assign, and discuss Multica issues. Also covers comments, subscribers, and viewing execution runs for an issue. Use when the user wants to file a task for an agent, triage the board, comment on an issue, or inspect what an agent actually did.
Route issue-running automation through a deterministic control plane that selects agent + model from registry, can coordinate multiple safe parallel agents, and executes the unified run-agent runner.
After solving a non-trivial problem, detect generalizable learnings and propose skill updates so future interactions benefit automatically. Always active — applies to every interaction.
Use this when users need to collect research materials for an article or topic by gathering YouTube videos and web articles into a NotebookLM notebook, then running analysis queries and saving the results as markdown. It is ideal for requests like "collect materials", "find relevant videos and articles on this topic for me", and "organize for NotebookLM analysis". This skill combines yt-dlp YouTube search, NotebookLM `nlm` CLI research, and markdown report output.
Expert guide for the NotebookLM CLI (`nlm`) - a command-line interface for Google NotebookLM. Use this skill when users want to interact with NotebookLM programmatically, including: creating/managing notebooks, adding sources (URLs, YouTube, text, Google Drive), generating content (podcasts, reports, quizzes, flashcards, mind maps, slides, infographics, videos, data tables), conducting research, chatting with sources, or automating NotebookLM workflows. Triggers on mentions of "nlm", "notebooklm", "notebook lm", "podcast generation", "audio overview", or any NotebookLM-related automation task.
Comprehensive codebase research skill. Documents codebase as-is by spawning parallel sub-agents and synthesizing findings into research documents.
Replace generic perspectives with domain-specific expert roles selected dynamically per request. Automatically picks the 3 most relevant experts from a role pool (Security, Performance, UX, Cost, DX, Architecture, etc.) based on the task context.
Configure and orchestrate Claude Code agent teams (TeamCreate, SendMessage, TaskUpdate workflow). Use when you need multiple agents working in parallel on a complex task, want to coordinate background agents with messaging, or are setting up a lead/teammate architecture with a shared task list. Teams are experimental — enable with --enable-teams flag.
Audit and optimize Claude Code configuration with dynamic best-practice research
Review a skill and extract deterministic, mechanical steps into shell scripts. Makes skills more reliable by separating precision work (scripts) from judgment work (AI). Use when asked to extract scripts from a skill, make a skill more deterministic, or split a skill into script + prompt.
Design exploration with parallel agents. Use when brainstorming ideas, exploring solutions, or comparing alternatives.