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Topic: llm

10,059 skills in this topic.

run-plan Plan the scope of a run by discovering available work items and suggesting groupings. Invoked before run-execute.
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run-status Display current run status and progress. Shows work item, mode, duration, and files changed.
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walkthrough-generate Generate implementation walkthrough for human review after run completion. Documents decisions, changes, and verification steps.
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project-init Initialize a new FIRE project by detecting workspace type and setting up standards.
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route Analyze project state and route user to the appropriate agent based on current context.
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status Display current FIRE project status and validate integrity of intents, work items, and runs.
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design-doc-generate Generate design documents for Validate mode work items (Checkpoint 1). Required for high-complexity items.
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intent-capture Capture user intent through guided conversation. Exploratory phase with high degrees of freedom.
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work-item-decompose Break an intent into discrete, executable work items with complexity assessment and dependency validation.
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flame Multi-perspective idea evaluation using Six Hats analysis, impact/feasibility scoring, and collaborative shortlisting.
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forge Shape top ideas into actionable concept briefs using Disney Strategy — Dream, Reality, Critique.
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spark Rapid idea generation with cross-domain diversity, anti-bias enforcement, and deep thinking.
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ask-questions-if-underspecified Clarify requirements before implementing. Do not use automatically, only when invoked explicitly.
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decomplect-py Architectural code analysis for Python design quality. Evaluates simplicity (Rich Hickey), functional core/imperative shell (Gary Bernhardt), and coupling (Constantine & Yourdon). Use for design review or architectural assessment of Python code.
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tasks-system
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ask-questions-if-underspecified Clarify requirements before implementing. Do not use automatically, only when invoked explicitly.
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decomplect-py Architectural code analysis for Python design quality. Evaluates simplicity (Rich Hickey), functional core/imperative shell (Gary Bernhardt), and coupling (Constantine & Yourdon). Use for design review or architectural assessment of Python code.
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tasks-system
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connect Find connections between notes and update MOCs. Requires semantic judgment to identify genuine relationships. Use after /extract creates notes, when exploring connections, or when a topic needs synthesis. Triggers on "/connect", "/connect [note]", "find connections", "update MOCs", "connect these notes".
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extract Extract structured knowledge from source material. Two modes — `extract` (default) for comprehensive atomic claim extraction, and `analyze` for design proposals where one impact-analysis note replaces claim decomposition. A relevance filter ("does this change how we build our project?") applies to all modes. For `extract` mode on domain-relevant sources, skip rate must be below 10%. Triggers on "/extract", "/extract [file]", "extract insights", "mine this", "process this".
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graph Interactive knowledge graph analysis. Routes natural language questions to graph scripts, interprets results in domain vocabulary, and suggests concrete actions. Triggers on "/graph", "/graph health", "/graph triangles", "find synthesis opportunities", "graph analysis".
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learn Research a topic and grow your knowledge graph. Uses Exa deep researcher, web search, or basic search to investigate topics, files results with full provenance, and chains to processing pipeline. Triggers on "/learn", "/learn [topic]", "research this", "find out about".
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next Surface the most valuable next action by combining task stack, queue state, inbox pressure, health, and goals. Recommends one specific action with rationale. Triggers on "/next", "what should I do", "what's next".
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pipeline End-to-end source processing -- seed, reduce, process all claims through reflect/revisit/review, archive. The full pipeline in one command. Triggers on "/pipeline", "/pipeline [file]", "process this end to end", "full pipeline".
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