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/major/porkbun-mcp/copilot-instructionsgit clone --depth 1 https://github.com/major/porkbun-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/major/porkbun-mcp/copilot-instructions)<a href="https://agentmods.dev/instructions/major/porkbun-mcp/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/major/porkbun-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 | $0.00824 | $0.00824 |
| Opus 5 | $0.00412 | $0.00412 |
| Sonnet 5 | $0.00165 | $0.00165 |
| Haiku 4.5 | $0.00082 | $0.00082 |
Grade A, and why
porkbun-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 6d 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Copilot Code Review Instructions
Review Philosophy: Invert, Always Invert
Apply Charlie Munger's inversion principle: Instead of asking "Is this code good?", ask "What would make this code fail?"
Focus on preventing failure rather than achieving brilliance:
- What edge cases would break this?
- What would cause this to fail in production?
- What would make this unmaintainable in 6 months?
- What security holes does this open?
When something could fail, explain HOW it would fail and suggest the prevention.
Project Context: porkbun-mcp
MCP (Model Context Protocol) server for Porkbun DNS API. Python 3.14+, FastMCP 2.14+.
Tech Stack
- MCP Framework: FastMCP 2.14+
- DNS Client: oinker (async-first)
- Type checking: ty
- Linting/Formatting: ruff
- Testing: pytest + pytest-asyncio
- Package manager: uv
Key Design Decisions
- MCP Resources for read-only data browsing
- Unified tools (one
dns_createwithrecord_typeparam) - Strict output schemas via Pydantic response models
Inversion Checklists by File Type
Source Code (src/porkbun_mcp/**/*.py)
MCP server failures to prevent:
- Tools not returning proper Pydantic response models
- Not handling oinker exceptions (must convert to
ToolError) - Blocking calls in async tool functions
- Missing type hints or docstrings
FastMCP patterns to enforce:
- Tools use
@mcp.tool()decorator with proper type hints - Resources use
@mcp.resource()decorator - Context accessed via
ctx.request_context.lifespan_context - Errors raised as
ToolErrororResourceError
Tools (src/porkbun_mcp/tools/**/*.py)
What would cause tools to fail?
- Not using oinker's
create_record()factory for DNS creation - Exceptions not mapped to
ToolErrorviahandle_oinker_error() - Missing
Annotated[type, Field(...)]for parameter descriptions - Return type not matching declared Pydantic model
Resources (src/porkbun_mcp/resources/**/*.py)
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.
- 6d ago First seen · 107 lines · 824 tokens per session scan A 830a63f2ca84
porkbun-mcp copilot-instructions.md is an instructions file published in the GitHub repository major/porkbun-mcp (23 stars, last pushed 3mo ago), licensed MIT. It adds 824 tokens to every session, about $0.0041 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 2026-08-30.
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