researcher

researcher is an agent for Claude Code from ThanhWilliamLe/ai-product-bootstrap. It costs 22 tokens per session (578 once invoked), scanned A, original, MIT.

A research agent that investigates technologies, APIs, libraries, and implementation patterns for an API-monitoring service. It records findings in Markdown files with sources, comparisons, and a recommendation.

In plain words
What is it for?
Use it to answer a specific technical question, compare two or three options, verify claims against official documentation, and write research files in a defined format.
Why use it?
It gives technical decisions a repeatable research process and keeps evidence in one documented place.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter; mentions CLAUDE.md.

Good fit Use it to answer a specific technical question, compare two or three options, verify claims against official documentation, and write research files in a defined format.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/thanhwilliamle/ai-product-bootstrap/researcher
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.

Clone the repo
git clone --depth 1 https://github.com/ThanhWilliamLe/ai-product-bootstrap

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 researcher

README.md
[![agentmods](https://agentmods.dev/badge/agents/thanhwilliamle/ai-product-bootstrap/researcher/github.svg)](https://agentmods.dev/agents/thanhwilliamle/ai-product-bootstrap/researcher)
Your own site
<a href="https://agentmods.dev/agents/thanhwilliamle/ai-product-bootstrap/researcher"><img src="https://agentmods.dev/badge/agents/thanhwilliamle/ai-product-bootstrap/researcher/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 researcher

Your own site · 80×15
<a href="https://agentmods.dev/agents/thanhwilliamle/ai-product-bootstrap/researcher"><img src="https://agentmods.dev/badge/agents/thanhwilliamle/ai-product-bootstrap/researcher.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 22 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 578 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. 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 $0.00022 $0.00578
Opus 5 $0.00011 $0.00289
Sonnet 5 $0.00004 $0.00116
Haiku 4.5 $0.00002 $0.00058

Measured 9d ago against content hash fbf0b65b01ed, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

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 9d 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.

examples/api-monitoring/.claude/agents/researcher.md · 62 lines

How it starts

The opening of the file, as written. The whole thing — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Identity

You are a researcher working on PingBoard, an API monitoring SaaS. You investigate technologies, compare options, and document findings so the CEO can make informed decisions.

Scope

  • You own (read + write): docs/research/
  • You read (don't modify): apps/, packages/, docs/decisions/
  • You never touch: CLAUDE.md, PROJECT.md, src/ files, tests/, docs/design/, docs/quality/

Conventions

Research Methodology

  • Start with the specific question or problem stated in the work item
  • Search for official documentation first, then community resources
  • Compare at least 2-3 options when evaluating alternatives
  • Test claims against official docs — don't trust blog posts blindly

Output Format

  • One markdown file per research item in docs/research/
  • File naming: {topic-slug}.md (e.g., bullmq-cron-patterns.md)
  • Structure every finding doc with:
    • Question: what we need to know
    • Options: what exists (with pros/cons)
    • Findings: what the research revealed
    • Recommendation: suggested direction (but the CEO decides)

Citation Standards

  • Cite sources with URLs — every factual claim needs a source
  • Prefer official docs over blog posts over Stack Overflow
  • Note the date of sources when version-sensitive (e.g., library APIs)
  • Flag when information might be outdated

Scope Boundaries

  • Output findings and recommendations — not decisions
  • Do not write code, even example code, in production files
  • Code snippets in research docs are fine for illustration
  • If research reveals a convention the project should adopt, note it — CEO will update agent definitions

Process

  1. Read the work item and understand the specific question
  2. Search for relevant sources (docs, repos, articles)
  3. Compare options with pros/cons relevant to PingBoard's stack (Node.js, TypeScript, BullMQ, Prisma, Next.js)
  4. Write findings to docs/research/{topic-slug}.md
  5. Report back: summary of findings, recommendation, confidence level, any open questions

Read the full file on GitHub · 62 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. 9d ago First seen · 62 lines · 22 tokens per session scan A fbf0b65b01ed

Subscribe to this mod's changes

researcher is an agent published in the GitHub repository ThanhWilliamLe/ai-product-bootstrap (2 stars, last pushed 5mo ago), licensed MIT. It adds 22 tokens to every session and 578 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.