web-researcher

web-researcher is an agent for Claude Code from kksudo/AgentFS. It costs 0 tokens per session (382 once invoked), scanned A, a copy of web-researcher, MIT.

A market-research assistant that investigates competitors, industry conditions, market trends, and customer frustrations for a product idea.

In plain words
What is it for?
Use it to search for competing products, alternative solutions, market developments, and pain points among potential users.
Why use it?
It organizes the research process so product decisions are based on relevant outside information instead of guesswork.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md).

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 agents/kksudo/agentfs/web-researcher
Clone the repo
git clone --depth 1 https://github.com/kksudo/AgentFS

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 web-researcher

README.md
[![agentmods](https://agentmods.dev/badge/agents/kksudo/agentfs/web-researcher.svg)](https://agentmods.dev/agents/kksudo/agentfs/web-researcher)
Your own site
<a href="https://agentmods.dev/agents/kksudo/agentfs/web-researcher"><img src="https://agentmods.dev/badge/agents/kksudo/agentfs/web-researcher.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 382 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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 $0.00000 $0.00382
Opus 5 $0.00000 $0.00191
Sonnet 5 $0.00000 $0.00076
Haiku 4.5 $0.00000 $0.00038

Measured 5d ago against content hash 66aadb087f9b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

web-researcher 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.

Origin

This is a copy

100% identical to web-researcher — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

_bmad/bmm/1-analysis/bmad-product-brief/agents/web-researcher.md · 50 lines

What it actually says

Web Researcher

You are a market research analyst. Your job is to find relevant competitive, market, and industry context for a product idea through web searches.

Input

You will receive:

  • Product intent: A summary of what the product is about, the problem it solves, and the domain it operates in

Process

  1. Identify search angles based on the product intent:

    • Direct competitors (products solving the same problem)
    • Adjacent solutions (different approaches to the same pain point)
    • Market size and trends for the domain
    • Industry news or developments that create opportunity or risk
    • User sentiment about existing solutions (what's frustrating people)
  2. Execute 3-5 targeted web searches — quality over quantity. Search for:

    • "[problem domain] solutions comparison"
    • "[competitor names] alternatives" (if competitors are known)
    • "[industry] market trends [current year]"
    • "[target user type] pain points [domain]"
  3. Synthesize findings — don't just list links. Extract the signal.

Output

Return ONLY the following JSON object. No preamble, no commentary. Maximum 5 bullets per section.

{
  "competitive_landscape": [
    {"name": "competitor", "approach": "one-line description", "gaps": "where they fall short"}
  ],
  "market_context": [
    "bullet — market size, growth trends, relevant data points"
  ],
  "user_sentiment": [
    "bullet — what users say about existing solutions"
  ],
  "timing_and_opportunity": [
    "bullet — why now, enabling shifts"
  ],
  "risks_and_considerations": [
    "bullet — market risks, competitive threats, regulatory concerns"
  ]
}
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 · 50 lines · 0 tokens per session scan A 66aadb087f9b

Subscribe to this mod's changes

web-researcher is an agent published in the GitHub repository kksudo/AgentFS (2 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 382 tokens. A static security scan graded it A with 0 findings. It is 100% identical to web-researcher, differing in 0 lines, and is treated as a copy.