Microsoft Discovery is an extensible platform for scientific research and research-and-development workflows that combines agent orchestration, reasoning, graph-based knowledge, and high-performance computing. Researchers, partners, and product users use its Azure enterprise platform or local Windows app to explore and build research workflows. The catalogue entries provide skills and instructions for working with the Discovery community and platform.
Borrowing it
Nothing to install: this file belongs to microsoft/discovery. 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/microsoft/discovery/main/utilities/supercomputer-cli/.github/copilot-instructions.mdgit clone --depth 1 https://github.com/microsoft/discoveryWrote 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/microsoft/discovery/copilot-instructions)<a href="https://agentmods.dev/instructions/microsoft/discovery/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/microsoft/discovery/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/microsoft/discovery/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/microsoft/discovery/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 | $0.02104 | $0.02104 |
| Opus 5.5 | $0.00842 | $0.00842 |
| Sonnet 5.5 | $0.00421 | $0.00421 |
| Haiku 4.5 | $0.00210 | $0.00210 |
Grade A, and why
discovery 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 — 244 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Copilot Instructions for Python API Polling Project
Project Context
This is a Python-based API polling application designed for portability across different environments (local development, Docker containers, and cloud platforms like Azure Discovery).
Code Style Guidelines
Python Standards
- Use Python 3.9+ features and type hints for all function signatures
- Follow PEP 8 naming conventions (snake_case for functions/variables, UPPER_CASE for constants)
- Use
pathlib.Pathinstead ofos.pathfor file operations - Prefer f-strings for string formatting
- Add docstrings to all functions using Google style format
Configuration Management
- Use environment variables for all configuration with sensible defaults
- Support both
.envfiles (via python-dotenv) and direct environment variables - Implement configuration precedence: CLI args > env vars > config files > defaults
- Use
pydanticSettings classes for configuration validation when possible
API Interaction Patterns
# Always use exponential backoff for retries
from tenacity import retry, stop_after_attempt, wait_exponential
@retry(stop=stop_after_attempt(3), wait=wait_exponential(min=1, max=10))
async def call_api(endpoint: str, **kwargs) -> dict:
"""Make API call with automatic retry logic."""
pass
Polling Implementation
- Use async/await patterns with
asynciofor efficient polling - Implement configurable poll intervals with jitter to avoid thundering herd
- Always include timeout mechanisms
- Log poll attempts and results at appropriate levels (DEBUG for success, WARNING for retries, ERROR for failures)
Error Handling
- Use custom exception classes for different error scenarios
- Always catch and log exceptions at the appropriate level
- Implement graceful shutdown handling (SIGTERM, SIGINT)
- Return meaningful exit codes (0=success, 1=general error, 2=config error, 3=connection error)
Logging
import logging
import sys
# Configure structured logging
logging.basicConfig(
level=logging.INFO,
format='[%(asctime)s] [%(name)s] [%(levelname)s] %(message)s',
handlers=[logging.StreamHandler(sys.stdout)]
)
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 · 244 lines · 2,104 tokens per session scan A 2f69e03ab3a3
discovery copilot-instructions.md is an instructions file published in the GitHub repository microsoft/discovery (267 stars, last pushed today), licensed MIT. It adds 2,104 tokens to every session, about $0.0084 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
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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.
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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).
deno copilot-instructions.md
Copilot instructions for denoland/deno, covering deno development guide for github copilot, network access, high level overview, key directories and key files to understand first.