k8s-gpu-mcp-server: Instructions file for GitHub Copilot

.github/copilot-instructions.md

k8s-gpu-mcp-server copilot-instructions.md is an instructions file for GitHub Copilot from ArangoGutierrez/k8s-gpu-mcp-server. It costs 1,896 tokens per session, scanned A, original, Apache-2.0.

A project instruction file for a Go service that inspects NVIDIA GPUs in Kubernetes through the Model Context Protocol, a standard way for tools to exchange structured messages with AI agents. It describes architecture, safety rules, and Go coding conventions.

In plain words
What is it for?
Use it when writing, reviewing, formatting, or testing code for this Kubernetes GPU diagnostic service.
Why use it?
It gives a coding agent the project-specific constraints needed to make safe diagnostic changes, including read-only defaults, minimal dependencies, and behavior when GPU hardware is unavailable.

Instructions file for GitHub Copilot

Written for GitHub Copilot: a Copilot instructions file.

This is ArangoGutierrez/k8s-gpu-mcp-server's own configuration. It tells GitHub Copilot how to work on k8s-gpu-mcp-server itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything k8s-gpu-mcp-server configures →

Reuse

Borrowing it

Nothing to install: this file belongs to ArangoGutierrez/k8s-gpu-mcp-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/ArangoGutierrez/k8s-gpu-mcp-server/main/.github/copilot-instructions.md
Clone the repo
git clone --depth 1 https://github.com/ArangoGutierrez/k8s-gpu-mcp-server

Made for: GitHub Copilot.

Wrote this? Show the measurements

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Per session 1,896 This file is loaded in full into every session.
When invoked 1,896 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.01896 $0.01896
Opus 5.5 $0.00758 $0.00758
Sonnet 5.5 $0.00379 $0.00379
Haiku 4.5 $0.00190 $0.00190

Measured 2mo ago against content hash 48af6f59b928, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

k8s-gpu-mcp-server 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 2mo 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.

.github/copilot-instructions.md · 279 lines

How it starts

The opening of the file, as written. The whole thing — 279 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GitHub Copilot Instructions for k8s-gpu-mcp-server

This file provides context and guidelines for GitHub Copilot when generating code, reviews, and suggestions for the k8s-gpu-mcp-server project.

Project Context

k8s-gpu-mcp-server is an ephemeral diagnostic agent that provides surgical, real-time NVIDIA GPU hardware introspection for Kubernetes clusters via the Model Context Protocol (MCP). It is designed for AI-assisted troubleshooting by SREs debugging complex hardware failures.

Key Architectural Principles

  1. Ephemeral Injection Pattern: No DaemonSets, no standing infrastructure
  2. Stdio Transport Only: JSON-RPC 2.0 over kubectl debug SPDY tunneling
  3. Read-Only Default: Safe operations with explicit operator mode for destructive actions
  4. Minimal Dependencies: Prefer standard library over third-party packages
  5. Hardware Safety: Isolate CGO/NVML calls, never panic on missing hardware

Code Generation Guidelines

Go Style and Conventions

  • Follow Effective Go principles strictly
  • Use gofmt -s (simplify) formatting
  • Documentation comments limited to 80 characters; wrap to multiple lines if needed
  • Always use context.Context as first parameter for I/O operations
  • Error wrapping with fmt.Errorf("context: %w", err) - preserve error chains
  • NO PANIC in production code (except main() initialization failures)

Error Handling Pattern

// Good: Contextual error with wrapping
if err := nvml.Init(); err != nil {
    return fmt.Errorf("failed to initialize NVML: %w", err)
}

// Bad: Silent failure or generic error
if err := nvml.Init(); err != nil {
    return err
}

Concurrency and Context

// Always pass context as first parameter
func GetGPUHealth(ctx context.Context, deviceIndex int) (*Health, error) {
    // Respect context cancellation
    select {
    case <-ctx.Done():
        return nil, ctx.Err()
    default:
    }
    
    // Use timeouts for hardware calls
    ctx, cancel := context.WithTimeout(ctx, 5*time.Second)
    defer cancel()
    
    // ... implementation
}

Read the full file on GitHub · 279 lines

Changes

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.

  1. 2mo ago First seen · 279 lines · 1,896 tokens per session scan A 48af6f59b928

Subscribe to this mod's changes

k8s-gpu-mcp-server copilot-instructions.md is an instructions file published in the GitHub repository ArangoGutierrez/k8s-gpu-mcp-server (5 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 1,896 tokens to every session, about $0.0076 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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