agents AGENTS.md

Repository instructions for tomzx/agents covering general writing rules, Python work, repository-specific guidance, machine settings, and GitHub CLI use.

In plain words
What is it for?
They guide concise writing, Python package and test practices, repository workflows, and command-line GitHub tasks.
Why use it?
They give the agent project-specific rules to follow, reducing inconsistent changes and missed checks.

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/tomzx/agents/agents-md
Clone the repo
git clone --depth 1 https://github.com/tomzx/agents

Made for: Codex, OpenCode.

Per session 748 This file is loaded in full into every session.
When invoked 748 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 $0.00748 $0.00748
Opus 5 $0.00374 $0.00374
Sonnet 5 $0.00150 $0.00150
Haiku 4.5 $0.00075 $0.00075

Measured 2d ago against content hash 94c7b1cf700a, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agents 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 · 42 lines

How it starts

The opening of the file, as written. The whole thing — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.

General

  • Be concise
  • Do not use em-dashes, use commas or parentheses instead
  • One sentence per line
  • Avoid using the following terms (unless it is the most appropriate): shape, honest, load bearing
  • When a skill explicitly recommends running another skill as an upstream/prerequisite (for example create-article recommending research-article when sources are not yet gathered), and you choose not to follow that recommendation, you must say so and give your reasoning before proceeding, so it can be course-corrected. Surfacing the deviation after the fact is not sufficient.

Python

  • Use uv for package management
  • When creating a project, always use the most recent Python LTS version
  • Use type hints
  • Use pytest for testing
  • Use ruff for linting/formatting
  • Run tests before committing
  • Run linter/formatter before committing
  • Create "green path" tests that cover the main functionality
  • Use structlog for logging
  • When adding dependencies, use uv add ... over adding the version directly to pyproject.toml
  • Keep init.py files minimal/empty, only for package initialization
  • Do NOT use/add all in init.py files

Per-repository instructions

  • Before working in a git repository, check for per-repository overrides stored outside that repository.
  • Find the skills library root by resolving the real path of this AGENTS.md (follow symlinks), then look in its repositories/ directory, which is a sibling of skills/.
  • Derive {owner}/{repository} from the current repository's GitHub remote URL.
  • If repositories/{owner}/{repository}/AGENTS.md exists, read and apply it together with these base instructions.
  • For forks, symlink repositories/{fork-owner}/{repository} to the upstream repositories/{owner}/{repository} so both resolve to the same instructions.

Per-machine instructions

  • Some machines carry local overrides that should not be shared (e.g. employer-specific conventions).
  • Find the skills library root by resolving the real path of this AGENTS.md (follow symlinks), then look in its machines/ directory, which is a sibling of skills/.
  • machines/*/ profiles are gitignored and exist only on the current machine. Read and apply every machines/*/AGENTS.md that is present, together with these base instructions.

Read the full file on GitHub · 42 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 · 42 lines · 748 tokens per session scan A 94c7b1cf700a

Subscribe to this mod's changes

agents AGENTS.md is an instructions file published in the GitHub repository tomzx/agents (5 stars, last pushed 5d ago), licensed MIT. It adds 748 tokens to every session, about $0.0037 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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