Borrowing it
Nothing to install: this file belongs to vhcg77/github-copilot-instructions. 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/vhcg77/github-copilot-instructions/main/.github/copilot-instructions.mdgit clone --depth 1 https://github.com/vhcg77/github-copilot-instructionsWrote 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/vhcg77/github-copilot-instructions/copilot-instructions)<a href="https://agentmods.dev/instructions/vhcg77/github-copilot-instructions/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/vhcg77/github-copilot-instructions/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/vhcg77/github-copilot-instructions/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/vhcg77/github-copilot-instructions/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 | $0.04815 | $0.04815 |
| Opus 5.5 | $0.01926 | $0.01926 |
| Sonnet 5.5 | $0.00963 | $0.00963 |
| Haiku 4.5 | $0.00481 | $0.00481 |
Grade A, and why
github-copilot-instructions 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 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.
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 — 496 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Copilot General Instructions
About Me
I am a Senior Data Scientist. My main focus is on developing robust, scalable, and maintainable data science solutions. I work with Python in Visual Studio Code. My expertise includes data cleaning, exploratory data analysis (EDA), statistical modeling, machine learning, and MLOps.
About This Project
This repository contains utilities for Gasco - a comprehensive data application built on Google Cloud Platform for inventory analysis and resource management. The project encompasses everything from data engineering and MLOps to frontend development.
Project Structure
/data: Raw and processed datasets, configuration files/notebooks: Jupyter notebooks for exploration (e.g.,analisis_exploratorio_inventario.ipynb)/src: Modular Python source code (data processing, utilities, documentation tools)/tests: Unit and integration tests using pytest/terraform: Infrastructure as Code for GCP deployment/.vscode: VS Code workspace configuration with GitHub Copilot integration/.github/instructions: Hierarchical instruction system for GitHub Copilot
Current Dataset Context
- Primary focus: Inventory analysis (
inventario_recursos_gasco_2025_06_25.csv) - Asset management: JSON data for assets tracking (
assets_gasco_2025_06_25.json) - Analysis outputs: Query analysis logs and structured reports
- Business domain: Resource inventory, asset tracking, operational analytics
Tech Stack
This project utilizes a modern, cloud-native tech stack centered around Python and Google Cloud Platform (GCP).
The specific technologies and libraries for a given task depend on the role being performed. You MUST refer to the detailed tech stack defined in the relevant file within the .github/instructions/roles/ directory (e.g., data-scientist.md, data-engineer.md, mlops-engineer.md, frontend-developer.md, cloud-architect.md, qa-engineer.md, visualization-engineer.md, business-analyst.md, project-manager.md).
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 · 496 lines · 4,815 tokens per session scan A 8e748f5d270b
github-copilot-instructions copilot-instructions.md is an instructions file published in the GitHub repository vhcg77/github-copilot-instructions (2 stars, last pushed 1y ago), licensed MIT. It adds 4,815 tokens to every session, about $0.0193 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 2026-08-31.
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AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
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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.
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).
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.