vibes AGENTS.md

vibes AGENTS.md is an instructions file for Codex, OpenCode from wandb/vibes. It costs 1,389 tokens per session, scanned A, original, Apache-2.0.

A repository instruction file that teaches coding agents how to collaborate, provide context, break down work, and think about system-wide effects.

In plain words
What is it for?
Use it to guide requests involving task decomposition, project context, trade-offs, and maintainable solutions.
Why use it?
It gives agents shared prompting and planning guidance for projects where several people or tools may contribute.

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

Made for: Codex, OpenCode.

Wrote 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.

agentmods badge for vibes AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/wandb/vibes/agents-md.svg)](https://agentmods.dev/instructions/wandb/vibes/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/wandb/vibes/agents-md"><img src="https://agentmods.dev/badge/instructions/wandb/vibes/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,389 This file is loaded in full into every session.
When invoked 1,389 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 $0.01389 $0.01389
Opus 5 $0.00694 $0.00694
Sonnet 5 $0.00278 $0.00278
Haiku 4.5 $0.00139 $0.00139

Measured 2d ago against content hash 648556194c69, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

vibes 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 · 226 lines

How it starts

The opening of the file, as written. The whole thing — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agentic Prompting Guide

General strategies for working effectively with AI coding assistants across all platforms (Claude, Gemini, GPT, etc.).

Core Principles

1. Treat AI as a Collaborative Partner

  • Share your thought process and constraints
  • Ask for alternatives and trade-offs
  • Build on AI suggestions iteratively

2. Provide Rich Context

  • Include relevant code, error messages, and project details
  • Mention your experience level and learning goals
  • Specify your environment (frameworks, tools, constraints)

3. Think in Systems

  • Break complex problems into smaller components
  • Consider interactions between different parts
  • Plan for scalability and maintainability

Universal Prompting Patterns

The STAR Method

Situation - Task - Action - Result

Situation: I'm building a React app with TypeScript
Task: Need to implement user authentication
Action: Show me how to create a login form with validation
Result: Should handle success/error states and redirect users

The 5W+H Framework

Who, What, When, Where, Why, How

Who: Junior developer learning Node.js
What: Build a REST API for a blog
When: Need it working by end of week
Where: Using Express.js and MongoDB
Why: Portfolio project for job applications
How: Step-by-step implementation with explanations

Chain of Reasoning

Ask the AI to show its thinking process:

"Think through this step by step:
1. What are the main challenges with this approach?
2. What are 3 different solutions?
3. What are the pros/cons of each?
4. Which would you recommend and why?"

Advanced Agentic Techniques

1. Role Assignment

Give the AI specific expertise:

"Act as a DevOps engineer with 10 years of AWS experience. 
How would you set up CI/CD for this Node.js application?"

2. Perspective Taking

Ask for multiple viewpoints:

"From a security perspective... From a performance perspective... From a maintainability perspective..."

3. Socratic Method

Let the AI guide your learning:

Read the full file on GitHub · 226 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 · 226 lines · 1,389 tokens per session scan A 648556194c69

Subscribe to this mod's changes

vibes AGENTS.md is an instructions file published in the GitHub repository wandb/vibes (37 stars, last pushed 1y ago), licensed Apache-2.0. It adds 1,389 tokens to every session, about $0.0069 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 2026-09-02.

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