agents AGENTS.md

A set of instructions for contributing to a repository of AI-agent skills. It explains the required AGENTS.md file, skill folders, metadata, and evaluation files that test when skills should run and what they do.

In plain words
What is it for?
Use it when creating a skill directory, writing its SKILL.md description, or defining functional and trigger tests in evals.json. It also explains the repository's structure and purpose.
Why use it?
It removes guesswork when adding or reviewing skills in that repository. Clear metadata and tests help agents choose the right skill and help maintainers check its behavior.

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

Made for: Codex, OpenCode.

Per session 1,013 This file is loaded in full into every session.
When invoked 1,013 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 $0.01013 $0.01013
Opus 5 $0.00507 $0.00507
Sonnet 5 $0.00203 $0.00203
Haiku 4.5 $0.00101 $0.00101

Measured 2d ago against content hash 7da23a6916b4, 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 · 107 lines

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.

AGENTS.md

This file provides guidance to AI agents when working with code in this repository.

What This Repo Is

A collection of personal AI agent skills conforming to the AgentSkills open standard. Each skill is a self-contained directory discoverable by any compatible AI agent. Skills are invoked via the agent's native skill mechanism when their description: frontmatter matches the user's intent.

Skill Structure

Every skill lives in its own top-level directory named after the skill:

<skill-name>/
  SKILL.md          # frontmatter (name, description) + full skill instructions
  evals/
    evals.json       # functional test cases: what the skill should do when triggered
    trigger_eval.json # trigger test cases: when the skill should/should not fire

SKILL.md frontmatter

---
name: <skill-name>          # must match the directory name
description: <trigger text> # what the agent reads to decide whether to invoke
---

The description: field is critical — it drives automatic invocation. It should include trigger phrases, use-case scope, and explicit exclusions for common false-positive queries.

evals/evals.json schema

{
  "skill_name": "<name>",
  "evals": [
    {
      "id": 1,
      "prompt": "<user input>",
      "expected_output": "<what the skill should produce>",
      "files": [],
      "assertions": []
    }
  ]
}

evals/trigger_eval.json schema

An array of { "query": "...", "should_trigger": true|false } objects. Include both positive examples (clear matches) and negative examples (common false positives that must NOT fire the skill).

Adding a New Skill

  1. Create <skill-name>/SKILL.md with frontmatter and instructions.
  2. Create <skill-name>/evals/evals.json with at least 2–3 functional test cases.
  3. Create <skill-name>/evals/trigger_eval.json with a mix of positive and negative trigger examples — negative examples are especially important to prevent the skill from firing on superficially similar queries.
  4. Create <skill-name>/.claude-plugin/plugin.json with skill metadata.
  5. Add @./<skill-name>/SKILL.md to GEMINI.md.
  6. Run ln -s ../../<skill-name> .agents/skills/<skill-name> and commit the symlink.
  7. Add an entry to .claude-plugin/marketplace.json under plugins[].

Read the full file on GitHub · 107 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 · 107 lines · 1,013 tokens per session scan A 7da23a6916b4

Subscribe to this mod's changes

agents AGENTS.md is an instructions file published in the GitHub repository jzfgo/agents (1 stars, last pushed 3mo ago), licensed MIT. It adds 1,013 tokens to every session, about $0.0051 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.