Borrowing it
Nothing to install: this file belongs to raffertyuy/github-copilot-prompts. 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/raffertyuy/github-copilot-prompts/main/.claude/skills/generate-copilot-instructions/SKILL.mdgit clone --depth 1 https://github.com/raffertyuy/github-copilot-promptsWrote 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/skills/raffertyuy/github-copilot-prompts/generate-copilot-instructions)<a href="https://agentmods.dev/skills/raffertyuy/github-copilot-prompts/generate-copilot-instructions"><img src="https://agentmods.dev/badge/skills/raffertyuy/github-copilot-prompts/generate-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/skills/raffertyuy/github-copilot-prompts/generate-copilot-instructions"><img src="https://agentmods.dev/badge/skills/raffertyuy/github-copilot-prompts/generate-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 | $0.00016 | $0.00451 |
| Opus 5.5 | $0.00006 | $0.00180 |
| Sonnet 5.5 | $0.00003 | $0.00090 |
| Haiku 4.5 | $0.00002 | $0.00045 |
Grade A, and why
generate-copilot-instructions 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 — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Repository Analysis & Instruction System Generator
Overview
You are an expert AI system architect tasked with analyzing the current repository and creating a comprehensive instruction system with specialized persona prompt files that work across both Claude Code and GitHub Copilot.
Primary Objectives
- Analyze Repository: Examine the current codebase, architecture, dependencies, and project structure
- Generate CLAUDE.md: Create contextually appropriate instructions based on the code analysis (with both @import and markdown link syntax for cross-compatibility)
- Generate .claude/rules/: Create path-specific rules for different file types found in the repo
- Generate .github/instructions/: Create GitHub Copilot equivalents of the rules
- Create Skills: Build specialized skill files for different workflows
Required Analysis Steps
1. Repository Deep Dive
Perform a comprehensive analysis of:
- Language & Framework Detection: Identify primary programming languages, frameworks, libraries, and dependencies
- Architecture Patterns: Analyze code structure, design patterns, architectural decisions
- Project Type: Determine if it's a web app, API, mobile app, desktop app, library, etc.
- Build System: Identify build tools, package managers, CI/CD configurations
- Code Quality: Assess testing frameworks, linting rules, code organization
2. Generate Files
Create the following cross-compatible file structure:
CLAUDE.md # Main instructions (both tools)
.claude/
prompt-snippets/ # Shared prompt text
rules/ # Claude Code path-specific rules
skills/ # Shared skills
agents/ # Claude Code agents
.github/
copilot-instructions.md # GitHub Copilot instructions
instructions/ # GitHub Copilot path-specific rules
Execution
- Analyze the repository thoroughly
- Generate all files following the cross-compatibility patterns
- Ensure prompt snippets are the single source of truth
- Test that references between files are correct
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 · 47 lines · 16 tokens per session scan A e3927c6d0527
generate-copilot-instructions is a skill published in the GitHub repository raffertyuy/github-copilot-prompts (43 stars, last pushed 7mo ago), licensed MIT. It adds 16 tokens to every session and 451 once invoked, about $0.0001 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 2026-09-01.
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