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Found 504 Skills
Form a committee of two high-reasoning agents to step back, do root cause analysis, and produce a plan. Use when stuck, looping, tunnel-visioning, or facing a hard planning problem.
Symphony turns project work into isolated, autonomous implementation runs, allowing teams to manage work instead of supervising coding agents.
CrewAI task design and configuration. Use when creating, configuring, or debugging crewAI tasks — writing descriptions and expected_output, setting up task dependencies with context, configuring output formats (output_pydantic, output_json, output_file), using guardrails for validation, enabling human_input, async execution, markdown formatting, or debugging task execution issues.
Set up Jetty for the first time. Guides the user through account creation, API key configuration, and introduces runbooks — human-readable markdown files that tell an agent how to accomplish multi-step tasks with measurable outcomes. Use this skill whenever the user wants to set up, configure, or get started with Jetty — including 'set up jetty', 'configure jetty', 'jetty setup', 'get started with jetty', 'install jetty', 'connect to jetty', 'jetty onboarding', 'I am new to jetty', 'how do I start with jetty', or even just 'jetty' if they do not appear to have a token yet. Also trigger if the user mentions needing an API key for Jetty or storing their OpenAI/Gemini key in Jetty.
Repository understanding and hierarchical codemap generation
Write node content documents. Read download.txt, integrate local materials for each node and write detailed, accurate, and complete Markdown documents. Each sub-agent processes one node in parallel, outputting a complete node document including overview, directory/mind map, flow chart, online image URL, and reference materials. Suitable for scenarios requiring systematic and structured content creation.
Runs an autonomous development loop with research and implementation modes. Use when orchestrating iterative research and implementation cycles with dots-based task tracking and git workflow automation.
Review the current session for errors, issues, snags, and hard-won knowledge, then update the rules/ files (or AGENTS.md if no suitable rule file exists) with actionable learnings.
Gemini CLI consultation workflow for coding agents. Use when technical tasks need Gemini consultation for decisions, planning, debugging, problem-solving, or pre-implementation guidance.
File-based knowledge persistence patterns: when to store discoveries, when to recall past solutions, and how to organize project memory. Activate when starting tasks, encountering errors, making decisions, or when context may be lost between sessions.
Session retrospective and codification. Run at the end of any significant session to extract learnings, update documentation, and create artifacts that make future sessions smoother. Invoke when: - Finishing a multi-step implementation - After debugging a hard problem - End of any session with 3+ tool calls - "what did we learn?" / "wrap up" / "done" Subsumes /codify-learning (codification is one output, not the only one).
Multi-agent review of implementation plans. Use after creating a plan but before implementing, especially for complex or risky changes.