Skills that do not fit the categories above (14.2K skills)
Track and report agent invocation metrics including usage counts, success/failure rates, and completion times. Use for understanding which agents are utilized, identifying underused agents, and optimizing agent delegation patterns.
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Pre-commit and pre-merge validation checks. Use before committing changes or declaring work complete to ensure all quality gates pass.
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Maintain .agent state files. Use at session start, after meaningful steps, and before concluding: read/update constitution/memory/focus/issues/baseline consistently.
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Extract, plan, or propose implementation details at configurable depth levels (low/normal/extensive). Outputs to reference files for team discussion and handoff.
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Optimize agent instruction files by extracting sections into separate files and referencing them. Reduces context size while preserving information.
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Transform implementation plans into concise stakeholder-friendly summaries with file change overviews, component listings, and optional flow diagrams.
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Create new AgentOps skills via interactive interview. Supports from-scratch and clone modes with tiered complexity.
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Generate markdown reports from issues. Filter by type, priority, epic, date range. Supports summary, detailed, progress, completion, velocity, and backlog analysis views.
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Extract and display the final message from a Claude agent JSONL file. Use when the user wants to see an agent report, view agent output, extract agent results, check what an agent produced, or read the final response from a subagent. Triggers on requests like "show me agent report", "what did agent X produce", "extract agent output", "view agent results", or "get the report from agent ad42ecb".
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Agent skill for release-swarm - invoke with $agent-release-swarm
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Agent invocation syntax and boundary rules
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Evaluate agent performance using a structured scoring rubric
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Use this skill when the user asks to save, remember, recall, or organize memories. Triggers on: 'remember this', 'save this', 'note this', 'what did we discuss about...', 'check your notes', 'clean up memories'. Also use proactively when discovering valuable findings worth preserving.
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Real-time cost tracking, budget enforcement, and ROI measurement for AI agent operations. Track token usage, predict costs, enforce budget caps ($50-70/month typical), optimize model selection, cache results, measure cost-to-value. Use when tracking AI costs, preventing budget overruns, optimizing spend, measuring ROI, or ensuring cost-effective AI operations.
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Used to create a new agent. Used when a user wants to create a new agent
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Collect and synthesize opinions from multiple AI agents. Use when users say "summon the council", "ask other AIs", or want multiple AI perspectives on a question.
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Send and receive messages between AI agents using AI Maestro's messaging system. Use this skill when the user asks to "send a message", "check inbox", "read messages", "notify [agent]", "tell [agent]", or any inter-agent communication.
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Check agent configuration coverage across hierarchy levels and phases. Use to ensure complete agent system coverage.
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ユーザーの責任範囲定義から、Agentのマークダウンファイルを生成する。エージェント作成時、プラグイン要素生成時、またはユーザーがエージェント定義、責任範囲、Agent生成、エージェントドキュメントに言及した際に使用する。
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Retain and recall work context across sessions. Use when user asks to remember something, recall previous work, or reference past discussions. Triggered by phrases like 'remember this', 'save for later', 'recall', 'what did we discuss about'.
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Check and process messages from autonomous AILANG agents. Use when starting a session, after agent handoffs, or when checking for completion notifications.
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Structured cross-review protocol between specialized agents. Ensures scope alignment, priority calibration, and domain-aware feedback. Use when one agent reviews another's work, during handoffs, or when validating cross-cutting concerns.
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Use this skill to create or update the root AGENTS.md file to register AgenticDev skills for AI agent discovery. Triggers include "register AgenticDev", "update AGENTS.md", "setup agent guide", or initializing a new project.
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Add a new AI model to a provider (anthropic, openai, groq, cerebras). Use when a new model is announced and needs to be supported in aico.
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