Borrowing it
Nothing to install: this file belongs to Jamie-BitFlight/git-project-xray-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/Jamie-BitFlight/git-project-xray-mcp/main/.github/copilot-instructions.mdgit clone --depth 1 https://github.com/Jamie-BitFlight/git-project-xray-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/jamie-bitflight/git-project-xray-mcp/copilot-instructions)<a href="https://agentmods.dev/instructions/jamie-bitflight/git-project-xray-mcp/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/jamie-bitflight/git-project-xray-mcp/copilot-instructions/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/jamie-bitflight/git-project-xray-mcp/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/jamie-bitflight/git-project-xray-mcp/copilot-instructions.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 | $0.02759 | $0.02759 |
| Opus 5.5 | $0.01104 | $0.01104 |
| Sonnet 5.5 | $0.00552 | $0.00552 |
| Haiku 4.5 | $0.00276 | $0.00276 |
Grade C, and why
git-project-xray-mcp copilot-instructions.md scanned grade C with 1 finding 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 1mo 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
rm -rf dist/ build/ *.egg-info/ How it starts
The opening of the file, as written. The whole thing — 426 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Copilot Instructions for XRAY MCP
Repository Overview
XRAY is a Model Context Protocol (MCP) server providing progressive code intelligence for AI assistants. It uses ast-grep (tree-sitter powered) for structural code analysis without requiring language servers or databases.
Core Capabilities:
explore_repo- Progressive codebase exploration (directories → symbols)find_symbol- Fuzzy symbol search (functions, classes, methods)what_breaks- Reverse dependency analysis (find references)
Repository Stats:
- ~5MB source code (excluding .git and .venv)
- Primary language: Python 3.10+
- 4 Python source files in
src/xray/ - ~900 lines of core code (mcp_server.py + indexer.py)
- Stateless design with git-commit-based caching
Key Technologies:
- FastMCP (≥0.1.0) - MCP server framework
- ast-grep-cli (≥0.39.0) - Structural code search
- thefuzz (≥0.20.0) - Fuzzy string matching
- uv - Fast Python package manager (recommended)
Build & Installation Commands
Prerequisites
ALWAYS check these first:
python --version # Must be ≥3.10
uv --version # If not installed: pip install uv
Development Installation (RECOMMENDED)
Use this sequence for local development:
# 1. Create virtual environment (ALWAYS do this first)
uv venv
# 2. Install in editable mode (MUST be run from repo root)
uv pip install -e .
# 3. Verify installation
python -m xray.mcp_server --help
# Expected: FastMCP banner with "XRAY Code Intelligence" server name
CRITICAL: The server is an MCP server, NOT a CLI tool. It expects stdio communication from MCP clients. The --help output shows it's working but will wait for MCP protocol messages.
Building the Package
# Clean build (ALWAYS clean before building for distribution)
rm -rf dist/ build/ *.egg-info/
# Build package (takes ~30 seconds)
uv build
# Expected output:
# Successfully built dist/git_project_xray_mcp-VERSION.tar.gz
# Successfully built dist/git_project_xray_mcp-VERSION-py3-none-any.whl
# Verify artifacts
ls dist/
# Should show: .tar.gz and .whl files
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.
- 1mo ago First seen · 426 lines · 2,759 tokens per session scan C 7f229dfadf13
git-project-xray-mcp copilot-instructions.md is an instructions file published in the GitHub repository Jamie-BitFlight/git-project-xray-mcp (0 stars, last pushed 8mo ago), licensed MIT. It adds 2,759 tokens to every session, about $0.0110 per session on Opus 5.5. A static security scan graded it C with 1 finding (recursive force delete). It comes from a forked repository.
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