machineconfig: Instructions file for GitHub Copilot

.github/copilot-instructions.md

machineconfig copilot-instructions.md is an instructions file for GitHub Copilot from thisismygitrepo/machineconfig. It costs 1,598 tokens per session, scanned A, original, Apache-2.0.

A set of instructions for coding agents working on Python files in the machineconfig project. It defines how to run Python and tests, manage packages with uv, write temporary files, and follow the project's coding and privacy rules.

In plain words
What is it for?
Use it to guide Python development, test execution, dependency changes, temporary scripts, and safe repository navigation.
Why use it?
It keeps agent-generated Python work consistent with the repository's tools, file locations, and development conventions.

Instructions file for GitHub Copilot

Written for GitHub Copilot: a Copilot instructions file.

This is thisismygitrepo/machineconfig's own configuration. It tells GitHub Copilot how to work on machineconfig itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything machineconfig configures →

Reuse

Borrowing it

Nothing to install: this file belongs to thisismygitrepo/machineconfig. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/thisismygitrepo/machineconfig/main/.github/copilot-instructions.md
Clone the repo
git clone --depth 1 https://github.com/thisismygitrepo/machineconfig

Made for: GitHub Copilot.

Wrote 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.

agentmods badge for machineconfig copilot-instructions.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/thisismygitrepo/machineconfig/copilot-instructions/github.svg)](https://agentmods.dev/instructions/thisismygitrepo/machineconfig/copilot-instructions)
Your own site
<a href="https://agentmods.dev/instructions/thisismygitrepo/machineconfig/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/thisismygitrepo/machineconfig/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.

agentmods 80×15 button for machineconfig copilot-instructions.md

Your own site · 80×15
<a href="https://agentmods.dev/instructions/thisismygitrepo/machineconfig/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/thisismygitrepo/machineconfig/copilot-instructions.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 1,598 This file is loaded in full into every session.
When invoked 1,598 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.01598 $0.01598
Opus 5.5 $0.00639 $0.00639
Sonnet 5.5 $0.00320 $0.00320
Haiku 4.5 $0.00160 $0.00160

Measured 13d ago against content hash c9fc615c5c13, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

machineconfig 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 13d 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 · 91 lines

How it starts

The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.


applyTo: "**/*.py"

Python Development Environment and tooling:

  • Please run any python file using uv run $file.py
  • Same for tools, e.g. un run python pytest $file_path
  • To add a package, use cd $repo_root; uv add <package_name>.
    • Please never mention versions of package, so uv will bring the latest.
    • On this note, I have to say that I am seriously concerned about AI using very outdated coding style.
      • Use python 3.13 & 3.14 syntax features.
      • Use modern standards, e.g. Path from pathlib.
  • Never touch pyproject.toml manually, this file is strictly managed by uv tool on your behalf.
  • If you are writing a test or any temporary script for discovering or undestanding something as an intermediate step, then, please keep all your temp scripts and files under ./.ai/tmp_scripts directory, its included in .gitignore and won't litter the repo. Its also nice if you create a subdirectory therein to contain relevant files for the task at hand, to avoid confusion with other files from other ai agents working simulataneously on other things.
  • When you run a command in the terminal, please don't assume that it will run in the correct repo root directory. Always cd first to the repo root, or the desired directory, then run the command.

Python Coding Rules

  • Please type hint all the code. Use fully quilaified types, not just generics like dict, list, etc, rather dict[str, int], list[float], 'npt.NDarray[np.float32]', etc.
  • Please avoid the type Any, unless absoloutely necessary.
  • Please use # type: ignore blah blah, to silence any warning from pyright or other linters and type checkers, but only when necessary. Otherwise, listen to them and adjust accordingly, or use cast from typing.
  • Use typeddict, dataclasses and literals when necessary to avoid blackbox str or dict[str, str] etc.
  • ALL functions / methods etc must clearly indicate the return type in signature, even if its None.
  • Don't make file name types.py it conflicts with built-in modules.
  • Avoid from futures import annotations and the like, we are using python 3.13+ so no need for that.
  • Avoid writing code in init.py files, I hate black magic, avoid shims, and export files.
  • Avoid writing short functions with one or two lines, in-line instead.
  • Do not leave dangling imports or variables unused, prefix their name with underscore if necessary to indicate they are unused.
  • Please prefer to use absolute imports, avoid relatives when possible.
  • Use triple quotes and triple double quotes f-strings for string formatting and avoid when possible all goofy escaping when interpolation.
  • If needed, opt for polars not pandas, whenever possible.
  • when finished, run a linting static analysis check against files you touched, Any fix any mistakes.
  • Please run uv run -m pyright $file_touched and address all issues.
  • For all type checkers and linters, like mypy, pyright, pyrefly and pylint, there are config files at different levels of the repo all the way up to home directory level. You don't need to worry about them, just be mindful that they exist. The tools themselves will respect the configs therein.
  • If you want to run all linters and pycheckers agains the entire project to make sure everything is clean, I prepared a shared type-checking script, you can run it from the repo root as uv run ./scripts/type_checking/lint_and_type_check.py. It will produce markdown files that are you are meant to look at @ ./.ai/linters/*.md
  • Rust-inspired style, e.g.

Read the full file on GitHub · 91 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. 13d ago First seen · 91 lines · 1,598 tokens per session scan A c9fc615c5c13

Subscribe to this mod's changes

machineconfig copilot-instructions.md is an instructions file published in the GitHub repository thisismygitrepo/machineconfig (8 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 1,598 tokens to every session, about $0.0064 per session on Opus 5.5. 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 2026-10-02.

Related

Other instructions, from other repositories

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).

microsoft/vscode · 9,649 tokens

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.

vercel/next.js · 7,257 tokens

vscode oss-third-party-notices.instructions.md

Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).

microsoft/vscode · 5,262 tokens

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.

langchain-ai/langchain · 4,680 tokens

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.

deepseek-ai/deepseek-harness · 4,159 tokens

vscode copilot-instructions.md

Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).

microsoft/vscode · 2,731 tokens