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-resume)<a href="https://agentmods.dev/commands/nyldn/claude-octopus/octo-resume"><img src="https://agentmods.dev/badge/commands/nyldn/claude-octopus/octo-resume/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-resume"><img src="https://agentmods.dev/badge/commands/nyldn/claude-octopus/octo-resume.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 | $0.00018 | $0.00740 |
| Opus 5 | $0.00009 | $0.00370 |
| Sonnet 5 | $0.00004 | $0.00148 |
| Haiku 4.5 | $0.00002 | $0.00074 |
Grade B, and why
octo-resume scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
helper="$(find "${HOME}/.claude/plugins/cache" "${HOME}/Library/Application Support/Claude" "${LOCALAPPDATA:-/dev/null}/Claude" "${XDG_DATA_HOME:-${HOME}/.local/share}/Claude" -maxdepth 8 -path "*/nyldn-plugins/octo/*/sc Copies of this mod
1 near-identical copy found in the catalogue:
- resume — 91% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/octo:resume — Agent Resume
Your first output line MUST be: 🐙 Octopus Agent Resume
Resume a previously-running Claude agent by ID. Picks up the agent's transcript and continues where it left off.
MANDATORY COMPLIANCE — DO NOT SKIP
When the user explicitly invokes /octo:resume, you MUST call the agent-resume orchestrator path below. You are PROHIBITED from pretending to resume an agent from memory or starting unrelated fresh work without telling the user.
Step 1: Get the Agent ID
If you don't have the agent ID:
- Check
/octo:sentineloutput for running agent IDs - Look in
~/.claude-octopus/results/for recent result files (filename prefix contains agent type + task ID) - The agent ID was shown when the agent was originally spawned
Step 2: Resume
Use the Bash tool to execute:
Preflight check — Ensure plugin root is resolvable (run via Bash tool FIRST):
set -euo pipefail
OCTO_ROOT="${HOME}/.claude-octopus/plugin"
if [[ ! -x "$OCTO_ROOT/scripts/orchestrate.sh" ]]; then
helper="$OCTO_ROOT/scripts/helpers/ensure-plugin-root.sh"
if [[ ! -x "$helper" ]]; then
helper="$(find "${HOME}/.claude/plugins/cache" "${HOME}/Library/Application Support/Claude" "${LOCALAPPDATA:-/dev/null}/Claude" "${XDG_DATA_HOME:-${HOME}/.local/share}/Claude" -maxdepth 8 -path "*/nyldn-plugins/octo/*/scripts/helpers/ensure-plugin-root.sh" -print -quit 2>/dev/null)"
fi
[[ -x "$helper" ]] && bash "$helper" >/dev/null 2>&1 || true
fi
test -x "$OCTO_ROOT/scripts/orchestrate.sh" && echo "plugin-root:ok" || echo "plugin-root:missing"
If the output is plugin-root:missing, stop and ask the user to run /octo:setup.
${HOME}/.claude-octopus/plugin/scripts/orchestrate.sh agent-resume "$ARGUMENTS"
Pass the agent ID as $ARGUMENTS. Optionally append a follow-up prompt:
# Just agent ID (resumes with "Continue where you left off.")
orchestrate.sh agent-resume abc123
# Agent ID + custom prompt
orchestrate.sh agent-resume abc123 "fix the failing test in auth.ts"
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 · 72 lines · 18 tokens per session scan B 65fcb246dc45
octo-resume is a command published in the GitHub repository nyldn/claude-octopus (4,061 stars, last pushed yesterday), licensed MIT. It adds 18 tokens to every session and 740 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). 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.