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.
git 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/commands/nyldn/claude-octopus/octo-debate)<a href="https://agentmods.dev/commands/nyldn/claude-octopus/octo-debate"><img src="https://agentmods.dev/badge/commands/nyldn/claude-octopus/octo-debate/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/octo-debate"><img src="https://agentmods.dev/badge/commands/nyldn/claude-octopus/octo-debate.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 | $0.00012 | $0.00649 |
| Opus 5 | $0.00006 | $0.00324 |
| Sonnet 5 | $0.00002 | $0.00130 |
| Haiku 4.5 | $0.00001 | $0.00065 |
Grade A, and why
octo-debate 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 4d 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
2 near-identical copies found in the catalogue:
- debate — 91% identical, 4 lines differ
- octo-debate — 89% identical, 16 lines differ
How it starts
The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debate
Load skills/blocks/engineering-method-selection.md from the installed plugin
and apply only the methods relevant to this task. Preserve this entry point's
execution contract and output format. Read referenced skills as instructions;
do not invoke the current command recursively or add provider calls from a seat.
Structured AI debates between Claude and available external providers such as Codex, Antigravity, Grok, OpenCode, and OpenRouter.
🤖 INSTRUCTIONS FOR CLAUDE
MANDATORY COMPLIANCE — DO NOT SKIP
When the user explicitly invokes /octo:debate, you MUST execute the structured debate workflow below. You are PROHIBITED from answering the question directly, skipping the multi-provider debate, or deciding the topic is "too simple" for a provider debate. The user chose this command deliberately — respect that choice.
EXECUTION MECHANISM — NON-NEGOTIABLE
You MUST dispatch work to external providers (Codex, Antigravity, Grok, etc.) for this command. You are PROHIBITED from:
- ❌ Executing the entire task using only Claude-native tools
- ❌ Using a single Agent subagent instead of multi-provider dispatch
- ❌ Skipping provider dispatch because "I can handle this alone"
Multi-LLM orchestration is the purpose of this command. Single-model execution defeats its purpose.
Execution
- Follow the
skill-debateinstructions (Steps 1-7) exactly. - Start with Step 1: check provider availability and display the visual indicator banner.
- Step 2: ask clarifying questions via AskUserQuestion before proceeding.
- Steps 3-5: parse arguments, set up debate folder, conduct rounds with the selected participants (for example Codex CLI, Antigravity CLI, Grok CLI, Sonnet Agent, Claude/Opus).
- Steps 6-7: write final synthesis and present results to the user.
- Apply quality gates and cost tracking from
skill-debatethroughout.
Post-Completion — Interactive Next Steps
CRITICAL: After the debate completes, you MUST ask the user what to do next. Do NOT end the session silently.
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.
- 4d ago Changed · +5 lines 0056eeb72d68
- 7d ago First seen · 58 lines · 12 tokens per session scan A 7e02f0088a05
octo-debate is a command published in the GitHub repository nyldn/claude-octopus (4,061 stars, last pushed today), licensed MIT. It adds 12 tokens to every session and 649 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 2026-09-03.
Other commands, from other repositories
ai-context
Generate, update, or audit AI IDE context files with AGENTS.md as the canonical shared context and tool-specific bridge files. Signal Gate principle — only what agents cannot discover: $ARGUMENTS.
sync
Analyze codebase and populate knowledge-base with conventions, patterns, and technical debt.
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.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.