skill-extract — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited skill-extract (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
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 claimAutomated 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 quickCommon 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)
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.