research

research is a command for Claude Code from rjmurillo/ai-agents. It costs 15 tokens per session (1,014 once invoked), scanned A, original, MIT.

A command for researching an outside topic and turning the findings into project documentation and saved notes. It can use supplied web links as sources and connects the results to the project's existing knowledge systems.

In plain words
What is it for?
Use it to investigate a topic, write a 3,000–5,000-word analysis, map its relevance to the project, save durable notes, and create a GitHub issue when needed.
Why use it?
It turns scattered research into a structured analysis and identifies whether the findings require implementation work.

Command for Claude Code

Installs and runs on its own, but its text points at files inside its plugin — anything it tells you to read at a ${CLAUDE_PLUGIN_ROOT} path is only there once the plugin is installed. Installing the plugin gets both.

Part of the project-toolkit plugin — 95 skills, 26 commands, 33 agents, 4 hooks shipped together

Install

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.

agentmods
npx agentmods add commands/rjmurillo/ai-agents/research
Clone the repo
git clone --depth 1 https://github.com/rjmurillo/ai-agents

Made for: Claude Code.

Or install project-toolkit, the plugin that ships this one along with the rest of its 95 skills, 26 commands, 33 agents, 4 hooks.

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 research

README.md
[![agentmods](https://agentmods.dev/badge/commands/rjmurillo/ai-agents/research.svg)](https://agentmods.dev/commands/rjmurillo/ai-agents/research)
Your own site
<a href="https://agentmods.dev/commands/rjmurillo/ai-agents/research"><img src="https://agentmods.dev/badge/commands/rjmurillo/ai-agents/research.svg" alt="Measured on agentmods" height="20"></a>
Per session 15 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,014 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00015 $0.01014
Opus 5 $0.00008 $0.00507
Sonnet 5 $0.00003 $0.00203
Haiku 4.5 $0.00002 $0.00101

Measured 5d ago against content hash a08ee89a1f75, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade A, and why

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 5d 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.

.claude/commands/research.md · 86 lines

How it starts

The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research and Incorporate Command

ultrathink

Research external topics, create comprehensive analysis, and incorporate learnings into memory systems.

Usage

/research

Topic: {topic name}
Context: {why this matters to the project}
URLs: {optional comma-separated source URLs}

Parameters

Parameter Required Description
Topic Yes Subject to research
Context Yes Why this matters to the project
URLs No Source URLs to fetch and analyze

Example

/research

Topic: Chesterton's Fence
Context: Decision-making principle for understanding existing systems before changing them
URLs: https://fs.blog/chestertons-fence/, https://en.wikipedia.org/wiki/G._K._Chesterton

What This Does

  1. Research Phase: Check existing knowledge, fetch URLs, perform web searches
  2. Analysis Phase: Write 3000-5000 word analysis to .agents/analysis/
  3. Applicability Phase: Map integration points with ai-agents project
  4. Memory Phase: Create Serena memory + 5-10 atomic Forgetful memories
  5. Action Phase: Create GitHub issue if implementation work identified, via python3 "${COPILOT_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-.claude}}/skills/github/scripts/issue/new_issue.py"

Budget

Complete within 50k output tokens. If approaching the limit, summarize findings so far, persist partial analysis, and stop. Prefer completing fewer phases well over partial work across all phases.

Fallback Rules

  • If WebSearch returns no results for a query, try 2 alternative phrasings, then proceed with available information.
  • If a WebFetch URL is unreachable or returns a non-success status, note it as unavailable in the analysis and continue with other sources.
  • If memory systems (Serena or Forgetful) are unavailable, skip the Memory Phase and record the skip in the Action Phase output.
  • If a URL points at github.com, do not call WebFetch. Use the github skill scripts, which reach the API through gh and so cannot be denied by a WebFetch hook. Write the plugin root inline on each call, because shell variables do not survive between Bash invocations. Issue body and metadata: python3 "${COPILOT_PLUGIN_ROOT:-${CLAUDE_PLUGIN_ROOT:-.claude}}/skills/github/scripts/issue/get_issue_context.py" --owner {owner} --repo {repo} --issue {n}. Issue discussion: the same path with issue/get_issue_comments.py. PR body and diff: pr/get_pr_context.py --owner {owner} --repo {repo} --pull-request {n}. PR review discussion: pr/get_pr_review_comments.py and pr/get_pr_review_threads.py with the same flags.
  • If WebFetch is denied by a harness permission decision rather than a network error, that is a capability signal, not a prompt-injection attempt. Record the denial, switch to the github script path above for github.com URLs or to WebSearch for other hosts, and continue. Do not halt the run. Never call a tool the denial names unless it is already in this command's allowed-tools.

Read the full file on GitHub · 86 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. 5d ago First seen · 86 lines · 15 tokens per session scan A a08ee89a1f75

Subscribe to this mod's changes

research is a command published in the GitHub repository rjmurillo/ai-agents (45 stars, last pushed today), licensed MIT. It adds 15 tokens to every session and 1,014 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 2026-08-30.