Total 57,136 skills, AI & Machine Learning has 9506 skills
Showing 12 of 9506 skills
Discover, retrieve, and learn about available Agent Skills. key capability for finding tools to solve specific problems.
Optimize token usage when delegating to Gemini CLI. Covers token caching, batch queries, model selection (Flash vs Pro), and cost tracking. Use when planning bulk Gemini operations.
Use when evaluating AI tools and agentic workflows against workflow gaps, when conducting quarterly landscape scans, or when assessing integration feasibility of new tools for startup workflows.
Execute multiple independent tasks simultaneously using parallel agent coordination to maximize throughput. Use when tasks have no dependencies, results can be aggregated, and agents are available for concurrent work.
Brainstorm - Requirements Discovery (AI Coding Enhanced)
Sets up Claude Code agent teams with role-based composition. Use when creating dev teams, defining team roles, or organizing multi-agent collaboration. Do NOT use for single sub-agent creation (use agent-creator instead).
Analyze brownfield codebase and create initial continuity ledger
Create, validate, and convert skills for the agent ecosystem. Enforces standardized structure for consistency. Enables self-evolution by creating new skills on demand, converting MCP servers and codebases to skills.
Guide for creating Agent Skills: structure, best practices, and SKILL.md format for Claude Code, Codex, Gemini CLI, and other AI agents.
Fetches aggregated trace metrics (token usage, latency, trace counts, quality evaluations) from MLflow tracking servers. Triggers on requests to show metrics, analyze token usage, view LLM costs, check usage trends, or query trace statistics.
Submits and manages FastFold protein folding jobs via the Jobs API. Covers authentication, creating jobs, polling for completion, and fetching CIF/PDB URLs, metrics, and viewer links. Use when folding protein sequences with FastFold, calling the FastFold API, or scripting fold-and-wait workflows.
Sleep-time memory reflection: review recent conversations and daily notes, extract insights, and consolidate into long-term memory. Use when triggered by cron, heartbeat, or explicit request to reflect on recent activity. Runs as background processing to improve memory quality over time.