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Break a plan, spec, or conversation into dependency-aware, independently verifiable tickets. Use explicitly when the user wants work sliced for local planning or an issue tracker.

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Build a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.

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Synthesize an implementation-ready spec from the current conversation and relevant repository context. Use explicitly when the user wants agreed work captured as a spec or PRD.

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Map a large, unclear, multi-session effort as linked decisions, then advance the map until the route to the destination is clear.

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Implement work from a spec, ticket, or agreed conversation. Use explicitly when the user wants an existing plan carried through to working code.

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Configure repository-local tracker, triage, and domain-document conventions needed by the Matt Pocock engineering skills.

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Resolve an in-progress Git merge or rebase conflict while preserving the relevant intent of both sides. Use when conflict markers or an interrupted merge/rebase need investigation and resolution.

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Apply test-driven development with small, behavior-focused feedback loops. Use when the user asks to build or fix something test-first, mentions red-green-refactor, or wants integration tests.

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Analyze a codebase for high-leverage architectural improvements and explain evidence, tradeoffs, and next steps. Use explicitly for architecture audits or deep-module refactoring opportunities.

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Teach a skill or concept at the user's current level, optionally preserving a lightweight multi-session learning record.

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Investigate questions using high-trust primary sources and traceable citations. Use when the user asks for research, current documentation or API facts, source verification, or evidence-backed comparison.

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Classify and advance issues or external pull requests through the configured triage workflow. Use explicitly to inspect queues, evaluate an item, recommend a state, or apply an authorized transition.

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A relentless interview to sharpen a plan or design.

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A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.

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Design or revise concise skills with clear triggers, proportional constraints, progressive disclosure, and realistic validation.

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Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.

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Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".

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Search, create, and manage notes in the Obsidian vault with wikilinks and index notes. Use when user wants to find, create, or organize notes in Obsidian.

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Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.

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Show real token usage and estimated savings for the current session. Reads directly from the Claude Code session log — no AI estimation. Triggers on /caveman-stats. Output is injected by the mode-tracker hook; the model itself does not compute the numbers.

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Compact the current conversation into a handoff document for another agent to pick up.

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Discover installable agent skills from ctx's shipped Skills.sh catalog, the Skills.sh search API, and the npx skills CLI. Use when a user asks whether a skill exists, wants to add/update a skill, or needs a repeatable procedure for finding candidate skills safely.

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Ultra-compressed code review comments. Cuts noise from PR feedback while preserving the actionable signal. Each comment is one line: location, problem, fix. Use when user says "review this PR", "code review", "review the diff", "/review", or invokes /caveman-review. Auto-triggers when reviewing pull requests.

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Compress natural language memory files (CLAUDE.md, todos, preferences) into caveman format to save input tokens. Preserves all technical substance, code, URLs, and structure. Compressed version overwrites the original file. Human-readable backup saved as FILE.original.md. Trigger: /caveman-compress FILEPATH or "compress memory file"

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