Claude Octopus is an orchestration project that sends research, design, and coding tasks to Claude Code and other AI model providers so their results can be compared. Developers use it for multi-model work, disagreement detection, reviews, persistent context, and an optional workflow that moves from discovery through delivery. The catalogue entries are its commands, skills, agents, instructions, hooks, plugins, and settings.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add nyldn/claude-octopus --skill extract-skillgit clone --depth 1 https://github.com/nyldn/claude-octopusWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nyldn/claude-octopus/extract-skill)<a href="https://agentmods.dev/skills/nyldn/claude-octopus/extract-skill"><img src="https://agentmods.dev/badge/skills/nyldn/claude-octopus/extract-skill.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00019 | $0.01873 |
| Opus 5 | $0.00010 | $0.00937 |
| Sonnet 5 | $0.00004 | $0.00375 |
| Haiku 4.5 | $0.00002 | $0.00187 |
Grade A, and why
skill-extract scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- skill-extract — 92% identical, 9 lines differ
How it starts
The opening of the file, as written. The whole thing — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Extract Skill - Implementation Guide
Overview
The extract skill provides comprehensive reverse-engineering capabilities for design systems and product architectures. It transforms undocumented codebases into structured, implementation-ready documentation.
Capabilities
Design System Extraction
- Token Extraction: Colors, typography, spacing, shadows from code or CSS
- Component Analysis: Props, variants, usage patterns across React/Vue/Svelte
- Pattern Detection: Layout patterns, design rules, accessibility guidelines
- Storybook Generation: Auto-generated stories with variants and controls
Product Architecture Extraction
- Service Detection: Microservice boundaries, modules, domain boundaries
- API Mapping: REST, GraphQL, tRPC, gRPC endpoint cataloging
- Data Modeling: ORM schema extraction (Prisma, TypeORM, Sequelize)
- Feature Inventory: Route-based and domain-based feature detection
- C4 Diagrams: Automated architecture visualization (Mermaid)
Technical Implementation
Token Extraction Pipeline
Priority Order (High to Low Confidence):
- Code-Defined (95%):
theme.ts,tokens.json, Tailwind config - CSS Variables (90%):
:rootdeclarations - Computed Styles (60%): DOM analysis
- Inferred (40-60%): Color clustering, scale detection
Color Clustering Algorithm:
- Uses CIEDE2000 for perceptually-accurate color distance
- K-means++ initialization for stable clustering
- Default k=8 clusters for primary palettes
- ΔE < 2 threshold for duplicate detection
Component Analysis
Detection Strategies:
- AST parsing for TypeScript/JavaScript
- Prop extraction from interfaces and PropTypes
- Variant detection from union types
- Usage tracking across codebase
Supported Frameworks:
- React (functional, class, hooks)
- Vue (SFC, Composition API, Options API)
- Svelte (script/template separation)
Architecture Detection
Service Boundary Heuristics:
- Package.json in subdirectories
- Independent deployment configs
- Team ownership boundaries
- Communication pattern analysis
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 233 lines · 19 tokens per session scan A bdf6bba53648
skill-extract is a skill published in the GitHub repository nyldn/claude-octopus (4,056 stars, last pushed today), licensed MIT. It adds 19 tokens to every session and 1,873 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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ux-design-lead
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frontend-design
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brand-architect
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design-patterns
Modern design system patterns for 2025. Covers design tokens, OKLCH color systems, fluid typography, animations, dark mode, shadcn/ui components, and Figma handoff. Use when implementing UI styles, theming, accessibility, and visual polish.
canvas-design
Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.