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 skill-content-pipelinegit 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/skill-content-pipeline)<a href="https://agentmods.dev/skills/nyldn/claude-octopus/skill-content-pipeline"><img src="https://agentmods.dev/badge/skills/nyldn/claude-octopus/skill-content-pipeline/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/skills/nyldn/claude-octopus/skill-content-pipeline"><img src="https://agentmods.dev/badge/skills/nyldn/claude-octopus/skill-content-pipeline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00022 | $0.03398 |
| Opus 5 | $0.00011 | $0.01699 |
| Sonnet 5 | $0.00004 | $0.00680 |
| Haiku 4.5 | $0.00002 | $0.00340 |
Grade A, and why
skill-content-pipeline 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 13d 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.
How it starts
The opening of the file, as written. The whole thing — 590 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Pipeline Skill
Overview
Multi-stage pipeline for deep content analysis. Transforms external content into actionable patterns, anatomy guides, and recreatable frameworks.
┌─────────────────────────────────────────────────────────────────────────────┐
│ CONTENT ANALYSIS PIPELINE │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ Stage 1: URL Collection & Validation │
│ → Collect up to 5 reference URLs from user │
│ → Validate URLs (see skill-security-framing) │
│ → Apply platform transforms (Twitter → FxTwitter) │
│ ↓ │
│ Stage 2: Content Fetching & Sanitization │
│ → Fetch content via WebFetch │
│ → Wrap in security frame (MANDATORY) │
│ → Truncate if > 100K characters │
│ ↓ │
│ Stage 3: Pattern Deconstruction [Parallel Subagents] │
│ ├── Structure Analysis: Opening, body, closing patterns │
│ ├── Psychology Analysis: Persuasion, emotion, cognitive biases │
│ └── Mechanics Analysis: Headlines, sentences, formatting │
│ ↓ │
│ Stage 4: Anatomy Guide Synthesis │
│ → Merge all analyses into unified guide │
│ → Create structure blueprint │
│ → Build psychological playbook │
│ → Generate hook library │
│ ↓ │
│ Stage 5: Interview Question Generation │
│ → Identify what context is needed for recreation │
│ → Generate 8-12 targeted questions │
│ → Categorize by: Topic, Audience, Goals, Voice │
│ ↓ │
│ Stage 6: Output Generation │
│ → Save anatomy guide to session │
│ → Save interview questions │
│ → Optionally: Execute interview and generate variations │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
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.
- 13d ago First seen · 590 lines · 22 tokens per session scan A 0043701c9750
skill-content-pipeline is a skill published in the GitHub repository nyldn/claude-octopus (4,062 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 3,398 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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