Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/darbotlabs/darbot-deepmind-mcp/copilot-instructionsgit clone --depth 1 https://github.com/darbotlabs/Darbot-Deepmind-MCPWrote 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/darbotlabs/darbot-deepmind-mcp/copilot-instructions)<a href="https://agentmods.dev/instructions/darbotlabs/darbot-deepmind-mcp/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/darbotlabs/darbot-deepmind-mcp/copilot-instructions.svg" alt="Measured on agentmods" 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 | $0.01370 | $0.01370 |
| Opus 5 | $0.00685 | $0.00685 |
| Sonnet 5 | $0.00274 | $0.00274 |
| Haiku 4.5 | $0.00137 | $0.00137 |
Grade A, and why
Darbot-Deepmind-MCP 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 5d 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 — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Copilot Instructions for Darbot Deepmind MCP
This document provides guidance to GitHub Copilot when working on the Darbot Deepmind MCP Server project.
Project Overview
Darbot Deepmind MCP Server is a Model Context Protocol (MCP) server that provides advanced AI reasoning capabilities through a structured thinking framework. It enables sophisticated, step-by-step reasoning and problem-solving with dynamic thought processes and adaptive planning.
Technology Stack
- Language: TypeScript 5.9.3+ with strict type checking
- Runtime: Node.js 20.19.0 or higher
- Key Dependencies:
@modelcontextprotocol/sdk^1.26.0 - MCP protocol implementation@github/copilot-sdk^0.1.25 - GitHub Copilot integration (planned)zod^4.3.6 - Schema validationchalk- Console output formatting
- Testing: Jest 30 test framework
- Linting: ESLint 10 with flat config (eslint.config.mjs)
- Code Quality: ESLint and Prettier
Coding Standards
TypeScript Guidelines
- Use strict TypeScript settings - avoid
anytypes whenever possible - Provide explicit type annotations for function parameters and return values
- Leverage union types and generics appropriately
- Use
z.inferfor deriving types from Zod schemas - Prefer interfaces for object shapes, types for unions/intersections
Code Style
- Use 2 spaces for indentation (no tabs)
- Use meaningful, descriptive variable and function names
- Add JSDoc comments for all public methods and exported functions
- Follow the existing code structure and patterns
- Keep functions focused and single-purpose
Error Handling
- Use proper error handling with try/catch blocks
- Throw
McpErrorfor MCP-specific errors with appropriate error codes - Provide meaningful, actionable error messages
- Validate inputs using Zod schemas before processing
MCP Server Patterns
Tool Implementation
When implementing or modifying MCP tools:
- Define tools using the MCP SDK
Tooltype - Use Zod schemas for input validation
- Return structured responses with consistent formats
- Handle both successful and error cases explicitly
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.
- 5d ago First seen · 202 lines · 1,370 tokens per session scan A f160b8489b98
Darbot-Deepmind-MCP copilot-instructions.md is an instructions file published in the GitHub repository darbotlabs/Darbot-Deepmind-MCP (0 stars, last pushed 6mo ago), licensed MIT. It adds 1,370 tokens to every session, about $0.0068 per session on Opus 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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