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claude-octopus
claude-octopus には nyldn から収集した 105 個の skills があり、リポジトリ単位の職業カバレッジとサイト内 skill 詳細ページを表示します。
このリポジトリの skills
Reverse-engineer design systems, tokens, and components from live products or screenshots
Multi-AI requirements scoping using available external providers (Double Diamond Define phase)
Multi-AI validation, scoring, and review using available external providers (Double Diamond Deliver phase)
Multi-AI implementation using available external providers (Double Diamond Develop phase)
Multi-AI research using available external providers (Double Diamond Discover phase)
Decompose and execute large changes, migrations, or multi-issue fixes in parallel with quality gates
NLSpec authoring — use when you need a structured specification from multi-AI research and consensus
System architecture and API design with multi-AI consensus — use for design reviews and new subsystems
Expert multi-AI code review with inline PR comments — use for thorough quality and security analysis
Auto-detect work context (Dev vs Knowledge) — use to tailor workflows based on current task type
Structured multi-provider AI debates between Claude and available advisors — use for critical decisions
Thorough research across multiple sources — use for complex topics needing broad synthesis
Environment diagnostics — check providers, auth, config, hooks, scheduler, and more
Run a full build-and-ship pipeline from a spec — use for hands-off project generation
Route ordinary init, review, and security requests to Claude-native capabilities first; escalate to Octopus only when multi-LLM diversity adds value
Decompose large tasks across parallel agents — use for migrations, multi-file refactors, or batch work
Quick execution for ad-hoc tasks without full workflow overhead — use for small, self-contained requests
Package and finalize completed work for delivery — use when a feature is done and ready to ship
Review code in two passes: spec compliance then quality — use for thorough PR or feature reviews
Build features with tests-before-code rigor — use for new features needing test coverage
Design UI/UX systems with style guides, palettes, typography, and component specs for new interfaces
Evidence before claims — run verification commands before declaring work complete, fixed, or passing
Multi-AI requirements scoping using available external providers (Double Diamond Define phase)
Multi-AI validation, scoring, and review using available external providers (Double Diamond Deliver phase)
Multi-AI implementation using available external providers (Double Diamond Develop phase)
Multi-AI research using available external providers (Double Diamond Discover phase)
Decompose and execute large changes, migrations, or multi-issue fixes in parallel with quality gates
NLSpec authoring — use when you need a structured specification from multi-AI research and consensus
System architecture and API design with multi-AI consensus — use for design reviews and new subsystems
Quick execution for ad-hoc tasks without full workflow overhead — use for small, self-contained requests
Thorough research across multiple sources — use for complex topics needing broad synthesis
Design UI/UX systems with style guides, palettes, typography, and component specs for new interfaces
Expert multi-AI code review with inline PR comments — use for thorough quality and security analysis
Auto-detect work context (Dev vs Knowledge) — use to tailor workflows based on current task type
Structured multi-provider AI debates between Claude and available advisors — use for critical decisions
Environment diagnostics — check providers, auth, config, hooks, scheduler, and more
Reverse-engineer design systems, tokens, and components from live products or screenshots
Run a full build-and-ship pipeline from a spec — use for hands-off project generation
Route ordinary init, review, and security requests to Claude-native capabilities first; escalate to Octopus only when multi-LLM diversity adds value
Decompose large tasks across parallel agents — use for migrations, multi-file refactors, or batch work