ai-research-arm: Command for Claude Code

.claude/commands/gen-research.md

gen-research is a command for Claude Code from guzus/ai-research-arm. It costs 51 tokens per session (5,246 once invoked), scanned A, original, MIT.

A research command that investigates a topic using original sources and writes the result as an HTML article. It first asks whether to run in the current chat or through a GitHub Actions workflow, which runs automated jobs in GitHub.

In plain words
What is it for?
It helps research a supplied topic, verify information, and save a finished article in the repository.
Why use it?
It provides a choice between a quicker local run and a longer remote run with deeper research, before starting the work.

Command for Claude Code

Written for Claude Code: argument-hint in frontmatter. Also seen: mentions subagents; names the AskUserQuestion tool.

This is guzus/ai-research-arm's own configuration. It tells Claude Code how to work on ai-research-arm itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ai-research-arm configures →

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is uv run python scripts/check_generative_research.py /tmp/gen-research.ara.md \.

Reuse

Borrowing it

Nothing to install: this file belongs to guzus/ai-research-arm. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/guzus/ai-research-arm/main/.claude/commands/gen-research.md
Clone the repo
git clone --depth 1 https://github.com/guzus/ai-research-arm

Made for: Claude Code.

Wrote 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.

agentmods badge for gen-research

README.md
[![agentmods](https://agentmods.dev/badge/commands/guzus/ai-research-arm/gen-research/github.svg)](https://agentmods.dev/commands/guzus/ai-research-arm/gen-research)
Your own site
<a href="https://agentmods.dev/commands/guzus/ai-research-arm/gen-research"><img src="https://agentmods.dev/badge/commands/guzus/ai-research-arm/gen-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.

agentmods 80×15 button for gen-research

Your own site · 80×15
<a href="https://agentmods.dev/commands/guzus/ai-research-arm/gen-research"><img src="https://agentmods.dev/badge/commands/guzus/ai-research-arm/gen-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 51 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 5,246 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00051 $0.05246
Opus 5.5 $0.00020 $0.02098
Sonnet 5.5 $0.00010 $0.01049
Haiku 4.5 $0.00005 $0.00525

Measured 21d ago against content hash 526275a3c116, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

gen-research scanned grade A 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 21d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- `curl -sL <url> -o /tmp/x.pdf && pdftotext /tmp/x.pdf - | head -c 60000`
.claude/commands/gen-research.md · 463 lines

How it starts

The opening of the file, as written. The whole thing — 463 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Generative Research

User-supplied topic: $ARGUMENTS

If the topic above is empty or just whitespace, ask the user for a topic and stop until they answer.

Step 1 — choose execution mode (always ask)

Use AskUserQuestion to ask the user how they want this run executed. DO NOT skip this prompt — the two modes have very different cost, latency, and depth profiles. Present these two options:

  • Run locally (in this chat) — ~5–15 min. Deep pipeline runs in the current session using sub-agents (Task tool), evidence packets, and a verifier pass. Article lands as a local commit in research/generative/ (not pushed). Recommended for topics you want to iterate on, or when you want to read the result immediately.
  • Route to GitHub workflow — ~20–45 min on the self-hosted runner. Dispatches generative-research.yml on the registry's default backend (the generative-research-default lane in data/agent-backends.json) unless the user names one. Your chat is freed instantly. The runner produces a longer article (4500–7000 words target, ≥20 cited references) and publishes it to main. Recommended for substantive topics where you want maximum depth without spending in-chat time.

After the user picks:

  • Route → follow PATH A below.
  • Run locally → follow PATH B below.

PATH A — Route to the GitHub workflow

Dispatch the workflow with the user's topic. The backend comes from data/agent-backends.json, never from memory: omit -f backend and the workflow runs the generative-research-default lane. Pass -f backend=<selector> only when the user named one, and only if it matches a selector, backend key or alias in the registry; otherwise show the list and ask.

jq -r '.lanes["generative-research-default"].backend' data/agent-backends.json
# Selectable backends: selector, backend key, display name, aliases
jq -r '.backends | to_entries[] | select(.value.generative.exposed == true)
  | [.value.generative.selector, .key, .value.display_name,
     (((.value.aliases // []) + (.value.generative.aliases // [])) | join(","))] | @tsv' \
  data/agent-backends.json

DISPATCHED_AT="$(date -u +%Y-%m-%dT%H:%M:%SZ)"; echo "$DISPATCHED_AT"
gh workflow run generative-research.yml \
  -f topic='<the exact topic the user gave>'

Read the full file on GitHub · 463 lines

Changes

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.

  1. 21d ago Changed · +22 lines 526275a3c116
  2. 2mo ago First seen · 441 lines · 51 tokens per session scan A 0595240ee5c4

Subscribe to this mod's changes

gen-research is a command published in the GitHub repository guzus/ai-research-arm (14 stars, last pushed today), licensed MIT. It adds 51 tokens to every session and 5,246 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

gen-research compared with commands from other repositories

gen-research next to 6 commands from other repositories
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gen-researchguzus/ai-research-armCommand14todayMITA51Claude Code
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start-11-3minicoohei/ai-agent-campCommand3471mo agononeB2Claude Code
doctoropensesh/KARIMOCommand29024d agoApache-2.0A0Claude Code
greptile-reviewopensesh/KARIMOCommand29024d agoApache-2.0A0Claude Code
pi-code-reviewtznthou/claude-prismCommand10yesterdayMITA17Claude Code