gitlab-mcp copilot-instructions.md

A set of coding rules for the GitLab MCP Project, a Python project that connects coding agents to GitLab. It covers Python version, formatting, type annotations, code structure, and documentation.

In plain words
What is it for?
Use it when adding or reviewing Python code in the GitLab MCP Project, especially when choosing types, organizing imports, or designing functions and classes.
Why use it?
It gives an agent consistent project standards to follow, reducing style disagreements and code that conflicts with the repository’s checks.

Instructions file for GitHub Copilot

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.

agentmods
npx agentmods add instructions/adit-999/gitlab-mcp/copilot-instructions
Clone the repo
git clone --depth 1 https://github.com/Adit-999/gitlab-mcp

Made for: GitHub Copilot.

Per session 903 This file is loaded in full into every session.
When invoked 903 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
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 $0.00903 $0.00903
Opus 5 $0.00451 $0.00451
Sonnet 5 $0.00181 $0.00181
Haiku 4.5 $0.00090 $0.00090

Measured 3d ago against content hash ccdd635afe07, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

gitlab-mcp copilot-instructions.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 3d 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.

.github/copilot-instructions.md · 79 lines

How it starts

The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GitLab MCP Project - GitHub Copilot Instructions

Core Principles

  • Target Python 3.13 with all code.
  • Adhere strictly to PEP8 for styling and PEP585 for type hinting with built-in generics.
  • Use double quotes for strings and docstrings as per project ruff configuration.
  • Follow 88 character line length limit as defined in project settings.
  • Prioritize explicitness over implicitness in all code.
  • Follow the Principle of Least Surprise in API and interface design.
  • Avoid inline comments - prefer descriptive variable names and function names instead.

Code Structure

  • Favor small, focused @dataclasses over complex or mutable classes.
  • Limit function arguments to maximum of 7 parameters as configured in pylint settings.
  • Enforce a maximum of 30 statements per function per pylint configuration.
  • Use typestate and fluent interfaces where appropriate for ergonomic usage.
  • Organize imports according to the isort configuration with order: future, standard-library, third-party, first-party, local-folder.
  • Combine imports with the same namespace (e.g., from package import Class1, Class2).

Type System

  • Require specific type annotations throughout, using Python 3.13 features.
  • Use pathlib for all file path operations as enforced by the PTH linting rule.
  • Use Protocol classes for structural typing when interfaces matter more than inheritance.
  • Prefer Pydantic models (v2.11+) over unstructured containers for data validation.

Documentation

  • Follow Google-style docstrings as specified in the pydocstyle convention.
  • Document all public functions, classes, and methods with proper docstrings.
  • Include type information in docstrings consistent with annotations.
  • Mark TODOs with proper format that can be detected by the TD linting rule.
  • Place explanatory comments on separate lines before code, never inline with code.

API Design

  • Use Pydantic models for all external input and output validation.
  • Ensure consistent, structured error responses with clear codes and messages.
  • Follow the Model Context Protocol (MCP) standards for server implementation.
  • Design clean, resource-oriented APIs following RESTful principles.

Read the full file on GitHub · 79 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. 3d ago First seen · 79 lines · 903 tokens per session scan A ccdd635afe07

Subscribe to this mod's changes

gitlab-mcp copilot-instructions.md is an instructions file published in the GitHub repository Adit-999/gitlab-mcp (8 stars, last pushed 1y ago), licensed MIT. It adds 903 tokens to every session, about $0.0045 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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