Total 31,294 skills, AI & Machine Learning has 5070 skills
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This skill guides creating autonomous agents for Claude Code plugins using markdown files with YAML frontmatter. Use when building new agents, designing agent system prompts, or configuring agent behavior.
Use MiniMax MCP for image understanding and analysis. Trigger conditions: (1) Users request to analyze images, understand images, describe image content (2) Need to identify objects, text, and scenes in images (3) Use MiniMax's understand_image feature
Expert MLOps engineering covering model deployment, ML pipelines, model monitoring, feature stores, and infrastructure automation.
Workflow orchestration for complex coding tasks. Use for ANY non-trivial task (3+ steps or architectural decisions) to enforce planning, subagent strategy, self-improvement, verification, elegance, and autonomous bug fixing. Triggers: multi-step implementation, bug fixes, refactoring, architectural changes, or any task requiring structured execution.
Coordinate complex work using a phase-gated, multi-agent engineering loop (audit → design → implement → review → validate → deliver). Use when you need to split a task into subsystems, run dual independent audits, reconcile findings into a confirmed issue list, delegate fixes in clusters, enforce dual-review PASS gates, and drive an end-to-end delivery. Prefer discovering and invoking other specialized skills when they can execute part of the work faster or more reliably.
Use MiniMax MCP for web search. Trigger conditions: (1) User requests web search, online search, information lookup (2) Need to query the latest news, information, materials (3) Use MiniMax's web_search function
Use after completing work sessions to analyze agent behavior patterns, prepare session handoffs for continuity, document completed work, identify blockers, or preserve context for the next session.
Deeply analyzes Agent Studio framework structural health: catching phantom require() references, wrong module depth paths, missing skill/agent dependencies, bloated configurations, archived references in active code, stale catalog counts, and empty tool/skill directories.
AI image generation and editing using Google Gemini models (Nano Banana). Use when the user asks to generate an image, create an image, edit an image, or references "nano banana", "nanobanana", or "gemini image". Supports text-to-image, image editing, multi-image references, and 1K/2K/4K resolution.
Reviews chapter quality with checker agents and generates reports. Use when the user asks for a chapter review or runs /webnovel-review.
Meta-orchestrator (L0): reads kanban board, lets user pick ONE Story, drives it through pipeline 300->310->400->500 via TeamCreate. User-confirmed merge to develop after quality gate PASS.
Universal context reviewer: delegates arbitrary context (plans, decisions, documents, architecture proposals) to external agents (Codex + Gemini) for independent review with debate protocol. Context always passed via files.