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/CES-Ltd/LumiWrote 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/ces-ltd/lumi/octo-research)<a href="https://agentmods.dev/commands/ces-ltd/lumi/octo-research"><img src="https://agentmods.dev/badge/commands/ces-ltd/lumi/octo-research/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/ces-ltd/lumi/octo-research"><img src="https://agentmods.dev/badge/commands/ces-ltd/lumi/octo-research.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 | $0.00009 | $0.01078 |
| Opus 5 | $0.00005 | $0.00539 |
| Sonnet 5 | $0.00002 | $0.00216 |
| Haiku 4.5 | $0.00001 | $0.00108 |
Grade A, and why
octo-research 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 11d 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research - Deep Multi-AI Research
Your first output line MUST be: 🐙 Octopus Research
🤖 INSTRUCTIONS FOR CLAUDE
MANDATORY COMPLIANCE — DO NOT SKIP
When the user explicitly invokes /octo:research, you MUST execute the structured research workflow below. You are PROHIBITED from answering directly, skipping the multi-provider research, or deciding the topic is "too simple" for deep research. The user chose this command deliberately — respect that choice.
EXECUTION MECHANISM — NON-NEGOTIABLE
You MUST execute this command by invoking the corresponding skill via the Skill tool. You are PROHIBITED from:
- ❌ Using the Agent tool to research/implement yourself instead of invoking the skill
- ❌ Using WebFetch/Read/Grep as a substitute for multi-provider dispatch
- ❌ Skipping
orchestrate.shcalls because "I can do this faster directly" - ❌ Implementing the task using only Claude-native tools (Agent, Write, Edit)
Multi-LLM orchestration is the purpose of this command. If you execute using only Claude, you've violated the command's contract.
When the user invokes this command (e.g., /octo:research <arguments>):
Step 1: Ask Research Intensity
CRITICAL: Before starting research, use the AskUserQuestion tool to select intensity:
AskUserQuestion({
questions: [
{
question: "How thorough should the research be?",
header: "Research Intensity",
multiSelect: false,
options: [
{label: "Quick (1-2 min)", description: "2 agents — fast problem space scan"},
{label: "Standard (2-4 min)", description: "4-5 agents — balanced multi-perspective coverage (recommended)"},
{label: "Deep (3-6 min)", description: "6-7 agents — exhaustive analysis with web search"}
]
}
]
})
Map the answer to an intensity value:
- "Quick" →
quick - "Standard" →
standard - "Deep" →
deep
Step 2: Invoke Skill with Intensity
✓ CORRECT - Use the Skill tool:
Skill(skill: "octo:discover", args: "[intensity=quick|standard|deep] <user's arguments>")
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.
- 11d ago First seen · 130 lines · 9 tokens per session scan A 37f71e137c48
octo-research is a command published in the GitHub repository CES-Ltd/Lumi (31 stars, last pushed 4mo ago), licensed MIT. It adds 9 tokens to every session and 1,078 once invoked, about $0.0000 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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