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
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add nyldn/claude-octopus/plugin install octoWrote 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/commands/nyldn/claude-octopus/extract)<a href="https://agentmods.dev/commands/nyldn/claude-octopus/extract"><img src="https://agentmods.dev/badge/commands/nyldn/claude-octopus/extract/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/nyldn/claude-octopus/extract"><img src="https://agentmods.dev/badge/commands/nyldn/claude-octopus/extract.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00024 | $0.12004 |
| Opus 5 | $0.00012 | $0.06002 |
| Sonnet 5 | $0.00005 | $0.02401 |
| Haiku 4.5 | $0.00002 | $0.01200 |
Grade A, and why
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 7d 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.
This is a copy
95% identical to octo-extract — 4 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 1,548 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/octo:extract - Design System & Product Reverse-Engineering
Your first output line MUST be: 🐙 Octopus Extract
🤖 INSTRUCTIONS FOR CLAUDE
When the user invokes this command (e.g., /octo:extract <target> or /octo:extract <target>):
Step 0: PDF Page Selection (if target is PDF)
CRITICAL: For PDF files > 10 pages, ask user which pages to extract:
// Check if target is a PDF file
if (target.endsWith('.pdf') && isFile(target)) {
// Use Claude Octopus PDF page selection utility
const pageCount = await getPdfPageCount(target);
if (pageCount > 10) {
console.log(`📄 Large PDF detected: ${pageCount} pages`);
console.log(`Reading all pages may use ${pageCount * 750} tokens (~${Math.ceil(pageCount/133)} API calls).`);
const selection = await AskUserQuestion({
questions: [{
question: `This PDF has ${pageCount} pages. Which pages would you like to extract?`,
header: "PDF Pages",
multiSelect: false,
options: [
{label: "First 10 pages", description: "Quick overview (pages 1-10)"},
{label: "Specific pages", description: "Enter custom page range"},
{label: "All pages", description: `Full document (~${Math.ceil(pageCount/133)} API calls)`}
]
}]
});
let pageParam = "";
if (selection === "First 10 pages") {
pageParam = "1-10";
} else if (selection === "Specific pages") {
pageParam = await askForInput("Enter page range (e.g., 1-5, 10, 15-20):");
}
// else "All pages" - use empty string
// Store for use in extraction phases
target = { path: target, pages: pageParam };
console.log(`✓ Will extract pages: ${pageParam || 'all'}`);
}
}
Example output:
📄 Large PDF detected: 45 pages
Reading all pages may use 33,750 tokens (~34 API calls).
┌─────────────────────────────────────────────────────────┐
│ This PDF has 45 pages. Which pages would you like to │
│ extract? │
│ │
│ ● First 10 pages │
│ Quick overview (pages 1-10) │
│ │
│ ○ Specific pages │
│ Enter custom page range │
│ │
│ ○ All pages │
│ Full document (~34 API calls) │
└─────────────────────────────────────────────────────────┘
✓ Will extract pages: 1-10
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.
- 7d ago First seen · 1,548 lines · 24 tokens per session scan A b83dc49b91d6
extract is a command published in the GitHub repository nyldn/claude-octopus (4,061 stars, last pushed today), licensed MIT. It adds 24 tokens to every session and 12,004 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to octo-extract, differing in 4 lines, and is treated as a copy.
Other commands, from other repositories
theme
Switch between visual theme skins — OLED Black, Matrix, Claude Anthropic, Surprise Me.
stark-director
Use this command when the user asks Stark to go all out, raise design quality broadly, use libraries well, make a UI feel actually designed, or coordinate research, typography, motion, usability, implementation, and QA in one pass.
diagram
Generate architecture diagrams using Mermaid or PlantUML C4 for visual documentation.
hig-tokens
Emit Apple HIG design tokens (system colors light/dark, the iOS type ramp, spacing, corner radii, control sizes, contrast) in a chosen format.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.