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-discipline)<a href="https://agentmods.dev/commands/nyldn/claude-octopus/octo-discipline"><img src="https://agentmods.dev/badge/commands/nyldn/claude-octopus/octo-discipline/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-discipline"><img src="https://agentmods.dev/badge/commands/nyldn/claude-octopus/octo-discipline.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 | $0.00017 | $0.01087 |
| Opus 5 | $0.00009 | $0.00544 |
| Sonnet 5 | $0.00003 | $0.00217 |
| Haiku 4.5 | $0.00002 | $0.00109 |
Grade A, and why
octo-discipline scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- discipline — 97% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Discipline Mode
Toggle automatic skill invocation for development discipline.
Usage
/octo:discipline on — enable auto-invoke discipline checks
/octo:discipline off — disable (back to manual invoke only)
/octo:discipline status — show current state
What Discipline Mode Does
When on, you MUST follow these rules automatically — no user prompt needed:
Development Gates
1. Brainstorm gate — Before writing ANY code or making changes, check:
- Has the approach been discussed/planned? If not, read and follow the
skill-thought-partnerorskill-writing-planssource under${HOME}/.claude-octopus/plugin/.claude/skills/. - This applies even for "simple" changes
2. Verification gate — Before saying "done", "fixed", "passing", or committing, read and follow skill-verification-gate:
- Run the actual verification command, read output, only claim success with evidence
3. Review gate — After completing any non-trivial code change, automatically:
- Spec compliance check + code quality review via subagent
4. Response gate — When receiving code review feedback, read and follow skill-review-response:
- Verify feedback against actual code before implementing
5. Investigation gate — When encountering ANY bug, error, or test failure, read and follow skill-debug:
- Root cause investigation before proposing fixes
Knowledge Work Gates
6. Context gate — At the start of any task, detect dev vs knowledge work. If research, writing, design, or strategy — switch to KM mode. Use skill-context-detection.
7. Decision gate — When comparing options or evaluating trade-offs, present a structured comparison with criteria and scores — not just prose pros/cons. Use skill-decision-support.
8. Intent gate — Before any creative or writing task (README, docs, copy, design), lock in the goal and audience first. Validate output against locked goals. Use skill-intent-contract.
How It Works
When the user runs /octo:discipline on, persist the setting:
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 · 115 lines · 17 tokens per session scan A c5b8af7e1123
octo-discipline is a command published in the GitHub repository nyldn/claude-octopus (4,062 stars, last pushed today), licensed MIT. It adds 17 tokens to every session and 1,087 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
sdd-init
Initialize SDD context — detects project stack and bootstraps persistence backend.
extend
Capture a mid-PR sub-idea and implement it onto the current open PR's branch — no new branch, no new PR. Preserves Verify → Review → Deliver.
sparc-refinement-optimization-mode
🧹 Optimizer - You refactor, modularize, and improve system performance. You enforce file size limits, dependenc...
integrity
Verify the cognitive toolkit's internal consistency and memory accuracy. The toolkit makes claims about its own structure, and memory makes claims about the world. This command checks both.
review
Code review based on git diff. Reviews staged/unstaged changes or a specific commit range for bugs, security issues, and code quality.
checklist
Generate a custom checklist for the current feature based on user requirements.