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.
curl -O https://raw.githubusercontent.com/ArangoGutierrez/k8s-gpu-mcp-server/main/.github/copilot-instructions.mdgit clone --depth 1 https://github.com/ArangoGutierrez/k8s-gpu-mcp-serverWrote 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/arangogutierrez/k8s-gpu-mcp-server/copilot-instructions)<a href="https://agentmods.dev/instructions/arangogutierrez/k8s-gpu-mcp-server/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/arangogutierrez/k8s-gpu-mcp-server/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/arangogutierrez/k8s-gpu-mcp-server/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/arangogutierrez/k8s-gpu-mcp-server/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 | $0.01896 | $0.01896 |
| Opus 5.5 | $0.00758 | $0.00758 |
| Sonnet 5.5 | $0.00379 | $0.00379 |
| Haiku 4.5 | $0.00190 | $0.00190 |
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.
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
- Ephemeral Injection Pattern: No DaemonSets, no standing infrastructure
- Stdio Transport Only: JSON-RPC 2.0 over
kubectl debugSPDY tunneling - Read-Only Default: Safe operations with explicit operator mode for destructive actions
- Minimal Dependencies: Prefer standard library over third-party packages
- 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.Contextas 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
}
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.
- 2mo ago First seen · 279 lines · 1,896 tokens per session scan A 48af6f59b928
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.
k8s-gpu-mcp-server copilot-instructions.md compared with instructions from other repositories
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|---|---|---|---|---|---|---|---|
| k8s-gpu-mcp-server copilot-instructions.mdArangoGutierrez/k8s-gpu-mcp-server | Instructions file | 5 | 5mo ago | Apache-2.0 | A | 1,896 | GitHub Copilot |
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