Borrowing it
Nothing to install: this file belongs to kenshiro-o/nagato-ai. 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/kenshiro-o/nagato-ai/main/CLAUDE.mdgit clone --depth 1 https://github.com/kenshiro-o/nagato-aiWrote 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/kenshiro-o/nagato-ai/claude-md)<a href="https://agentmods.dev/instructions/kenshiro-o/nagato-ai/claude-md"><img src="https://agentmods.dev/badge/instructions/kenshiro-o/nagato-ai/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/kenshiro-o/nagato-ai/claude-md"><img src="https://agentmods.dev/badge/instructions/kenshiro-o/nagato-ai/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 | $0.00821 | $0.00821 |
| Opus 5 | $0.00411 | $0.00411 |
| Sonnet 5 | $0.00164 | $0.00164 |
| Haiku 4.5 | $0.00082 | $0.00082 |
Grade A, and why
nagato-ai 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 10d 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Project Overview
Nagato-AI is a Python library for building multi-LLM AI agent systems. It supports OpenAI, Anthropic, Google Gemini, Groq, and DeepSeek models through a unified agent interface. Agents can be orchestrated via graphs (DAGs), chains (sequential pipelines), or mission/task runners.
Commands
# Install
uv sync
# Format (isort + Black, line-length 120)
make fmt
# Lint (pylint, threshold 6)
make lint
# Run all tests
make test
# Run tests with debug logging
make test-debug
# Run a single test file
uv run pytest tests/nagatoai_core/graph/test_graph.py
# Run a single test
uv run pytest tests/nagatoai_core/graph/test_graph.py::test_function_name
Architecture
Agents (nagatoai_core/agent/)
Abstract Agent base class with provider-specific implementations (OpenAI, Anthropic, Google, Groq, DeepSeek). Use create_agent() and get_agent_type() from factory.py to instantiate agents by model name. Each agent maintains conversation history and supports tool calling. message.py defines Exchange, Message, ToolCall, ToolResult.
Tools (nagatoai_core/tool/)
AbstractTool base class with a _run() method. Tools are registered in ToolRegistry which provides fuzzy name matching via Levenshtein distance. Tool providers (tool/provider/) generate LLM-specific schemas for each tool. Built-in tools live in tool/lib/ (audio, filesystem, human input, web scraping, video, time, Readwise).
Graphs (nagatoai_core/graph/)
DAG-based workflow execution. Graph manages nodes and edges with cycle detection. Node types: AgentNode, ToolNode, ToolNodeWithParamsConversion. Flow types compose nodes: SequentialFlow, ParallelFlow, ConditionalFlow, TransformerFlow, UnfoldFlow. Workflows can also be defined declaratively in XML via graph/plan/xml_parser.py. See graph/README.md for detailed graph documentation.
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.
- 10d ago First seen · 65 lines · 821 tokens per session scan A fd15f7cf0142
nagato-ai CLAUDE.md is an instructions file published in the GitHub repository kenshiro-o/nagato-ai (119 stars, last pushed 4mo ago), licensed MIT. It adds 821 tokens to every session, about $0.0041 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.
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