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Found 5,791 Skills
Load top-performing Shinka programs into agent context using `shinka.utils.load_programs_to_df`, and emit a compact Markdown bundle for iteration planning.
Orchestrate teams of parallel Claude Code sessions working on the same codebase. Handles task decomposition, agent coordination, context isolation, and merge strategies. Builds on worktree-manager for infrastructure.
Authors and structures professional-grade agent skills following the agentskills.io spec. Use when creating new skill directories, drafting procedural instructions, or optimizing metadata for discoverability. Don't use for general documentation, non-agentic library code, or README files.
Operate the external task-management CLI (tk) as source of truth for agent execution tracking. Invoke when any SPEC comes up for implementation, when the user asks to track tasks, check what to work on next, see task status, manage work dependencies, or close/abandon tasks. For coordination-tier artifacts (EPIC, VISION, JOURNEY), swain-design must decompose into child SPECs first — this skill tracks the children, not the container.
Use when setting up a new AI agent from scratch — asks 10 discovery questions, configures the correct files for the target system, tests integrations, and implements security guardrails
Bridge any AI agent backend to WeChat using the weixin-agent-sdk framework with simple Agent interface, login, and message loop.
Workflow creation, execution, and template management. Automates complex multi-step processes with agent coordination. Use when: automating processes, creating reusable workflows, orchestrating multi-step tasks. Skip when: simple single-step tasks, ad-hoc operations.
CrewAI agent design and configuration. Use when creating, configuring, or debugging crewAI agents — choosing role/goal/backstory, selecting LLMs, assigning tools, tuning max_iter/max_rpm/max_execution_time, enabling planning/code execution/delegation, setting up knowledge sources, using guardrails, or configuring agents in YAML vs code.
Build and deploy AI agents with CloudBase Agent SDK (TypeScript & Python). Implements the AG-UI protocol for streaming agent-UI communication. Use when deploying agent servers, using LangGraph/LangChain/CrewAI adapters, building custom adapters, understanding AG-UI protocol events, or building web/mini-program UI clients. Supports both TypeScript (@cloudbase/agent-server) and Python (cloudbase-agent-server via FastAPI).
Use after analyze-and-document has generated CLAUDE.md for an AI Studio project. Installs project-level Claude Code configuration — rules, skills, settings, and optionally agents, hooks, and MCP servers — into the .claude/ directory so that all future sessions have the right guardrails and workflows.
A fast Rust-based headless browser automation CLI with Node.js fallback that enables AI agents to navigate, click, type, and snapshot pages via structured commands.
AI-Native Issue-Driven development workflow. From GitHub Issue to merged PR: parse issue, explore codebase, design technical plan, execute with agent team, create PR, and cleanup. Use when a user wants to implement a GitHub Issue end-to-end: `/issue-flow #123` or `/issue-flow` to pick from open issues.