Borrowing it
Nothing to install: this file belongs to natnew/Awesome-Prompt-Engineering. 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/natnew/Awesome-Prompt-Engineering/main/.github/copilot-instructions.mdgit clone --depth 1 https://github.com/natnew/Awesome-Prompt-EngineeringWrote 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/natnew/awesome-prompt-engineering/copilot-instructions)<a href="https://agentmods.dev/instructions/natnew/awesome-prompt-engineering/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/natnew/awesome-prompt-engineering/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/natnew/awesome-prompt-engineering/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/natnew/awesome-prompt-engineering/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 | $0.01416 | $0.01416 |
| Opus 5.5 | $0.00566 | $0.00566 |
| Sonnet 5.5 | $0.00283 | $0.00283 |
| Haiku 4.5 | $0.00142 | $0.00142 |
Grade A, and why
Awesome-Prompt-Engineering 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Copilot Instructions
About this repository
Awesome-Prompt-Engineering is a curated awesome list and learning hub for prompt engineering, context engineering, and AI agents. It is content, not an application: the deliverable is high-quality, well-organised Markdown, published to GitHub Pages via Jekyll.
README.md is the index and the main list. Topic pages (Basic_Prompting.md,
Advanced_Prompting.md, AI_Tools.md, Resources.md, Articles.md, and others)
hold the longer-form content. Contribution rules live in Contributing.md,
Workflow.md, and code-of-conduct.md.
How to treat the repository
- Treat every change as a documentation edit. There is no build, test, or runtime behaviour to reason about beyond Markdown rendering.
- Make the smallest change that achieves the goal. Do not reformat, reorder, or rewrite existing content that the task does not touch.
- Preserve the maintainer's voice and the structure already in place.
Contribution standard
The list is mature, so the bar is high. A good addition is unique, broadly
useful, durable, and non-promotional. Per Contributing.md, projects should be
more than 30 days old and have at least 60 stars. Prefer canonical sources
(official docs, the primary repository, the original paper or guide) over
marketing pages, mirrors, or aggregators.
Reviewing suggested additions
When assessing a new entry, check that it:
- is genuinely relevant to prompt engineering, context engineering, or AI agents;
- is not already listed — search the whole repository for the URL and the name before recommending it;
- links to a canonical, HTTPS source;
- has a neutral, factual description (no marketing taglines, no title-case), starting with a capital and ending with a full stop, and not beginning with "A" or "An";
- sits in the single best-fit existing category, added at the bottom of that category unless the section is alphabetised or otherwise ordered;
- matches the link style of the surrounding section (some lists use a hyphen, others an em dash — follow the local convention).
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 · 111 lines · 1,416 tokens per session scan A 69eb0fbaffd2
Awesome-Prompt-Engineering copilot-instructions.md is an instructions file published in the GitHub repository natnew/Awesome-Prompt-Engineering (114 stars, last pushed 5d ago), licensed MIT. It adds 1,416 tokens to every session, about $0.0057 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 2026-08-30.
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).
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.
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).
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.
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).
vscode model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.