Borrowing it
Nothing to install: this file belongs to fabao2024/LangGraph_Researcher. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/fabao2024/LangGraph_Researcher/main/CLAUDE.mdgit clone --depth 1 https://github.com/fabao2024/LangGraph_ResearcherWrote 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.
[](https://agentmods.dev/instructions/fabao2024/langgraph_researcher/claude-md)<a href="https://agentmods.dev/instructions/fabao2024/langgraph_researcher/claude-md"><img src="https://agentmods.dev/badge/instructions/fabao2024/langgraph_researcher/claude-md/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.
<a href="https://agentmods.dev/instructions/fabao2024/langgraph_researcher/claude-md"><img src="https://agentmods.dev/badge/instructions/fabao2024/langgraph_researcher/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.02195 | $0.02195 |
| Opus 5 | $0.01097 | $0.01097 |
| Sonnet 5 | $0.00439 | $0.00439 |
| Haiku 4.5 | $0.00219 | $0.00219 |
Grade A, and why
LangGraph_Researcher CLAUDE.md 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.
How it starts
The opening of the file, as written. The whole thing — 245 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md — LangGraph Researcher
This file provides guidance for AI assistants working in this repository.
Project Overview
LangGraph Researcher is a ReAct (Reasoning + Acting) agent built with LangGraph and Google Gemini. It combines web search with four specialized developer tools — called ADK Skills — that help with software tasks like formatting commits, adding license headers, generating Pydantic models, and validating database schemas.
The agent is exposed via LangGraph's API server and communicates entirely through the LangGraph chat interface.
Repository Structure
LangGraph_Researcher/
├── langgraph_101.py # Agent entry point: LLM, tools, graph assembly
├── langgraph.json # LangGraph configuration (graph name, version)
├── requirements.txt # Python dependencies
├── verify_adk.py # Test suite for all ADK skills
├── .env.example # Required environment variables template
├── adk/
│ ├── __init__.py
│ ├── core.py # @skill decorator (wraps functions as LangChain tools)
│ └── skills/
│ ├── __init__.py # Re-exports all four skills
│ ├── git.py # format_commit_message
│ ├── compliance.py # add_license_header
│ ├── codegen.py # generate_pydantic_model
│ └── data.py # validate_schema
├── README.md # Documentation (Portuguese)
├── README.en.md # Documentation (English)
└── CHANGELOG.md # Version history (Keep a Changelog format)
Architecture
Agent (langgraph_101.py)
The agent is built with create_react_agent from langgraph.prebuilt. It:
- Uses
gemini-2.0-flashviaChatGoogleGenerativeAIwithtemperature=0.2 - Has a Portuguese-language system prompt instructing it to search before answering, cite sources, and use ADK tools when appropriate
- Exposes five tools to the LLM:
search_web— Tavily search (max 5 results, advanced depth)format_commit_message— Conventional Commits formatteradd_license_header— MIT license header injectorgenerate_pydantic_model— JSON → Pydantic convertervalidate_schema— DB schema governance checker
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.
- 9d ago First seen · 245 lines · 2,195 tokens per session scan A f970cd68c24e
LangGraph_Researcher CLAUDE.md is an instructions file published in the GitHub repository fabao2024/LangGraph_Researcher (5 stars, last pushed 6mo ago), licensed MIT. It adds 2,195 tokens to every session, about $0.0110 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.
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