research

research is a command for Claude Code from Achitokun14/claude-universal. It costs 26 tokens per session (406 once invoked), scanned A, original, MIT.

A command for researching a topic across multiple web sources and producing a brief with citations.

In plain words
What is it for?
Use it to create a cited research brief covering key findings, disagreements or gaps, and the sources consulted.
Why use it?
It reduces the manual work of searching, comparing, fetching, and organizing source material. It also includes library documentation searches when the topic involves a framework, library, or software development kit.

Command for Claude Code

Written for Claude Code: argument-hint in frontmatter.

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/achitokun14/claude-universal/research
Clone the repo
git clone --depth 1 https://github.com/Achitokun14/claude-universal

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 research

README.md
[![agentmods](https://agentmods.dev/badge/commands/achitokun14/claude-universal/research.svg)](https://agentmods.dev/commands/achitokun14/claude-universal/research)
Your own site
<a href="https://agentmods.dev/commands/achitokun14/claude-universal/research"><img src="https://agentmods.dev/badge/commands/achitokun14/claude-universal/research.svg" alt="Measured on agentmods" height="20"></a>
Per session 26 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 406 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 $0.00026 $0.00406
Opus 5 $0.00013 $0.00203
Sonnet 5 $0.00005 $0.00081
Haiku 4.5 $0.00003 $0.00041

Measured 5d ago against content hash 9a5e239f6f59, 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.

user/commands/research.md · 45 lines

What it actually says

Run a parallel research pass on $ARGUMENTS and produce a cited brief.

Steps:

  1. If $ARGUMENTS is empty, ask: "What's the research topic?".

  2. Dispatch these calls in parallel (single message, multiple tool calls):

    • WebSearch for $ARGUMENTS (broad)
    • mcp__duckduckgo__duckduckgo_web_search for $ARGUMENTS (cross-check)
    • If the topic mentions a library/framework/SDK, also:
      • mcp__plugin_context7_context7__resolve-library-id then query-docs
  3. From the search results, pick the top 3-5 distinct, high-quality URLs and dispatch parallel WebFetch on each (prompt: "Extract: main claim, key data points, limitations, date published, author credibility.").

  4. Synthesize into this format:

    # Research: $ARGUMENTS
    
    **Date:** YYYY-MM-DD | **Sources consulted:** N
    
    ## TL;DR
    <3-bullet summary>
    
    ## Key findings
    - <claim> — <source 1>
    - <claim> — <source 2>
    ...
    
    ## Contradictions / gaps
    - <where sources disagree or are silent>
    
    ## Sources
    1. <title> — <url> — <date> — <credibility note>
    2. ...
    
  5. Offer to save the brief to ~/Desktop/ACTIVITIES/llm-wiki/research/<slug>-$(date +%Y%m%d).md.

Never present unsourced claims as fact. If context7 has docs on the topic, cite them first.

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 · 45 lines · 26 tokens per session scan A 9a5e239f6f59

Subscribe to this mod's changes

research is a command published in the GitHub repository Achitokun14/claude-universal (2 stars, last pushed 2mo ago), licensed MIT. It adds 26 tokens to every session and 406 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 2026-08-31.