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Found 507 Skills
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).
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.
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.
Use when completing a task, implementing a feature, or before committing to verify work meets requirements and coding standards. Triggers: task completion, pre-commit check, pre-merge validation, plan alignment verification, post-refactor quality gate.
When multiple tests fail, assign each failing test file to a separate subagent that fixes it independently in parallel.
This skill enriches vague prompts with targeted research and clarification before execution. Should be used when a prompt is determined to be vague and requires systematic research, question generation, and execution guidance.
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.
Gemini CLI consultation workflow for coding agents. Use when technical tasks need Gemini consultation for decisions, planning, debugging, problem-solving, or pre-implementation guidance.
Multi-agent review of implementation plans. Use after creating a plan but before implementing, especially for complex or risky changes.
Define the design rules (Skill Laws) that all Skills must follow, including core principles such as AI-first, human-centric, and ready-to-use. When to use: When users create a new Skill, optimize an existing Skill, ask about Skill design specifications, or need to evaluate Skill quality.
Monitors context window health throughout a session and rides peak context quality for maximum output fidelity. Activates automatically after plan-interview and intent-framed-agent. Stays active through execution and hands off cleanly to simplify-and-harden and self-improvement when the wave completes naturally or exits via handoff. Use this skill whenever a multi-step agent task is underway and session continuity or context drift is a concern. Especially important for long-running tasks, complex refactors, or any work where degraded context would silently corrupt the output. Trigger even if the user doesn't say "context surfing" — if an agent task is running across multiple steps with intent and a plan already established, this skill is live.