snapcrab AGENTS.md

A set of coding instructions for the snapcrab project. It tells AI assistants and developers how to review changes, write tests, improve documentation, and handle errors.

In plain words
What is it for?
Guiding code changes, reviews, tests, documentation, and error-message improvements in the snapcrab codebase.
Why use it?
It gives contributors shared expectations for correctness and production-quality work instead of relying on personal preferences.

Instructions file for CodexOpenCode

Install

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.

agentmods
npx agentmods add instructions/celinval/snapcrab/agents-md
Clone the repo
git clone --depth 1 https://github.com/celinval/snapcrab

Made for: Codex, OpenCode.

Per session 1,627 This file is loaded in full into every session.
When invoked 1,627 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
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 $0.01627 $0.01627
Opus 5 $0.00813 $0.00813
Sonnet 5 $0.00325 $0.00325
Haiku 4.5 $0.00163 $0.00163

Measured 2d ago against content hash e67e4025a4da, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

snapcrab AGENTS.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 2d 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.

AGENTS.md · 180 lines

How it starts

The opening of the file, as written. The whole thing — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.

General guidelines

This document captures code conventions for the snapcrab project. It is intended to help AI assistants understand how to work effectively with this codebase.

Inspired by nextest's AGENTS.md.

For humans

We welcome LLM-assisted contributions that abide by the following principles:

  • Aim for excellence. Use LLMs as a quality multiplier. Invest the time savings in improving rigor beyond what you'd do alone. Refactor for clarity. Tackle the tedious parts. Aim for zero bugs.
  • Review like a mentor. Treat LLM output as you would code from someone you're mentoring. Read every line, question design decisions, and find ways to break it.
  • Write tests. Use LLMs to produce thorough tests — edge cases, boundary conditions, failure modes. Tests are where AI assistance pays off the most.
  • Improve docs and errors. Use LLMs to write clear documentation and actionable error messages. Users should never be left wondering what went wrong or what to do next.
  • Your code is your responsibility. Do not submit a first draft. If your PR shows signs of not being reviewed, we may decline it outright.

For LLMs

Correctness over convenience

  • Model the full error space. No shortcuts or simplified error handling.
  • Handle edge cases, including platform differences and overflow conditions.
  • Use the type system to encode correctness constraints.
  • Prefer compile-time guarantees over runtime checks where possible.

Production-grade engineering

  • Test comprehensively, including edge cases and boundary conditions.
  • Pay attention to what test facilities already exist and reuse them.
  • Getting the details right is really important.

Documentation

  • Keep documentation concise. Provide relevant information without overwhelming the reader — don't repeat yourself.
  • Doc comments (///) must start with a brief one-line summary. This first line is the title — keep it short and descriptive.
  • Use inline comments to explain "why," not just "what."
  • Don't add narrative comments in function bodies. Only comment what is non-obvious or needs a deeper "why" explanation.
    • Consider pulling the code to a separate function if it becomes too complex.
  • Module-level documentation (//!) should explain purpose and responsibilities.
  • Always use periods at the end of code comments.

Read the full file on GitHub · 180 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. 2d ago First seen · 180 lines · 1,627 tokens per session scan A e67e4025a4da

Subscribe to this mod's changes

snapcrab AGENTS.md is an instructions file published in the GitHub repository celinval/snapcrab (10 stars, last pushed 5d ago), licensed Apache-2.0. It adds 1,627 tokens to every session, about $0.0081 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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