Borrowing it
Nothing to install: this file belongs to azumausu/shogi-mcp. 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/azumausu/shogi-mcp/main/CLAUDE.mdgit clone --depth 1 https://github.com/azumausu/shogi-mcpWrote 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/azumausu/shogi-mcp/claude-md)<a href="https://agentmods.dev/instructions/azumausu/shogi-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/azumausu/shogi-mcp/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/azumausu/shogi-mcp/claude-md"><img src="https://agentmods.dev/badge/instructions/azumausu/shogi-mcp/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 | $0.00783 | $0.00783 |
| Opus 5 | $0.00392 | $0.00392 |
| Sonnet 5 | $0.00157 | $0.00157 |
| Haiku 4.5 | $0.00078 | $0.00078 |
Grade A, and why
shogi-mcp 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 — 70 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
This is a Shogi AI Engine wrapper that provides both REST API and MCP (Model Context Protocol) server interfaces for a Shogi engine. The project wraps a native Shogi engine binary to provide modern API access for AI-powered Shogi analysis.
Key Commands
Running the Services
- REST API Server:
npm run start:rest- Starts the REST API server on port 8787 (configurable via PORT env var) - MCP Server:
npm run start:mcp- Starts the MCP server for stdio communication - Install Dependencies:
npm install- Installs Express and MCP SDK dependencies
Environment Variables
ENGINE_PATH: Path to the Shogi engine binary (default:./engine/engine)PORT: REST server port (default: 8787)REST_BASE: MCP server's REST API base URL (default:http://localhost:8787)DEBUG: Set to "1" to enable engine communication debug logsEVAL_FILE: Optional path to evaluation file for the engineEVAL_DIR: Optional directory containing evaluation files
Architecture
Core Components
-
AIEngine Class (
engine.js):- Manages USI protocol communication with the native Shogi engine binary
- Handles engine lifecycle, position setup, and analysis requests
- Uses mutex for thread-safe sequential operations
- Parses engine info lines to extract evaluation data (score, PV, depth, etc.)
-
REST API Server (
rest.js):- Express server providing HTTP endpoints for engine analysis
- Main endpoint:
GET /analyzewith query parameters:sfen(required): Board position in SFEN formatdepth: Search depth (default: 30, max: 30)multipv: Number of best moves to analyze (default: 10, max: 10)threads: Engine threads (default: 1, max: 8)forceMove: Optional move to analyze after the given position
-
MCP Server (
mcp-server.mjs):- Implements Model Context Protocol for AI agent integration
- Provides three tools:
ping: Health check toolanalyze: Full position analysis with MultiPVeval_at: Evaluate position after a specific move
- Communicates with REST API internally
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 · 70 lines · 783 tokens per session scan A d144236081fb
shogi-mcp CLAUDE.md is an instructions file published in the GitHub repository azumausu/shogi-mcp (1 stars, last pushed 1y ago), licensed MIT. It adds 783 tokens to every session, about $0.0039 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.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.