npx claudepluginhub nyldn/claude-octopus --plugin octoThis skill uses the workspace's default tool permissions.
The `extract` skill provides comprehensive reverse-engineering capabilities for design systems and product architectures. It transforms undocumented codebases into structured, implementation-ready documentation.
Creates isolated Git worktrees for feature branches with prioritized directory selection, gitignore safety checks, auto project setup for Node/Python/Rust/Go, and baseline verification.
Executes implementation plans in current session by dispatching fresh subagents per independent task, with two-stage reviews: spec compliance then code quality.
Dispatches parallel agents to independently tackle 2+ tasks like separate test failures or subsystems without shared state or dependencies.
The extract skill provides comprehensive reverse-engineering capabilities for design systems and product architectures. It transforms undocumented codebases into structured, implementation-ready documentation.
Priority Order (High to Low Confidence):
theme.ts, tokens.json, Tailwind config:root declarationsColor Clustering Algorithm:
Detection Strategies:
Supported Frameworks:
Service Boundary Heuristics:
API Endpoint Detection:
When enabled, the extract feature uses multiple AI providers for higher accuracy:
Provider Roles:
Consensus Mechanism:
90_evidence/disagreements.mdoctopus-extract/
└── project-name/
└── timestamp/
├── README.md # Navigation and summary
├── metadata.json # Extraction parameters
│
├── 00_intent/
│ ├── answers.json # User intent responses
│ ├── intent-contract.md # Human-readable summary
│ └── detection-report.md # Stack auto-detection results
│
├── 10_design/
│ ├── tokens.json # W3C Design Tokens format
│ ├── tokens.css # CSS custom properties
│ ├── tokens.md # Human-readable token docs
│ ├── components.csv # Component inventory (tabular)
│ ├── components.json # Structured component data
│ ├── patterns.md # Layout and design patterns
│ └── storybook/ # Storybook scaffold (optional)
│ ├── .storybook/
│ └── stories/
│
├── 20_product/
│ ├── product-overview.md # What, who, key journeys
│ ├── feature-inventory.md # Features by domain
│ ├── architecture.md # C4 text description
│ ├── architecture.mmd # Mermaid C4 diagrams
│ ├── PRD.md # AI-agent executable PRD
│ ├── user-stories.md # Gherkin-style scenarios
│ ├── api-contracts.md # Endpoint specifications
│ ├── data-model.md # Entity relationships
│ └── implementation-plan.md # Phased milestones
│
└── 90_evidence/
├── quality-report.md # Coverage and confidence metrics
├── disagreements.md # Multi-AI conflicts
├── extraction-log.md # Timestamped progress log
└── references.json # File paths per claim
Automated validation ensures extraction quality:
/octo:extract ./my-app
/octo:extract ./my-app --mode design --storybook true
/octo:extract ./my-app --depth deep --multi-ai force
/octo:extract https://example.com --mode design --depth quick
Common error codes:
ERR-001: Invalid input (path/URL not found)ERR-002: Network timeout (URL extraction)ERR-003: Permission deniedERR-004: Out of memory (use --depth quick)VAL-001: Validation failed (no tokens detected)VAL-004: Low multi-AI consensus| Depth | Time Target | Coverage Target |
|---|---|---|
| Quick | < 2 min | 70% coverage, basic analysis |
| Standard | 2-5 min | 85% coverage, comprehensive |
| Deep | 5-15 min | 95% coverage, multi-AI validation |
This skill is informed by research on:
Current Version: 1.0.0 (Skeleton)
Implemented:
In Progress:
Planned:
See implementation plan in project documentation.
Implementation phases:
This skill implements the design specified in PRD v2.0 (AI-Executable)