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ai-product-planner: Instructions file for Codex

AGENTS.md

ai-product-planner AGENTS.md is an instructions file for Codex, OpenCode from codenameju/ai-product-planner. It costs 100 tokens per session, scanned A, original, MIT.

A set of instructions for an AI-assisted product-planning project. It covers product requirements, user flows, wireframes, structured agreements between parts of a system, and handoff through MCP, a way for tools to communicate with agents.

In plain words
What is it for?
It guides work on product plans, requirements, user flows, wireframes, public API changes, tests, and the supervisor-to-workers-to-integration workflow.
Why use it?
It gives coding agents rules for preserving the project's design, testing changes, handling secrets, and avoiding fake success responses.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md.

This is codenameju/ai-product-planner's own configuration. It tells Codex and OpenCode how to work on ai-product-planner itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ai-product-planner configures →

not rated 0repo 3mo ago A scan 100 tokens original MIT
View source ↗ codenameju/ai-product-planner
Reuse

Borrowing it

Nothing to install: this file belongs to codenameju/ai-product-planner. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/codenameju/ai-product-planner/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/codenameju/ai-product-planner

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 ai-product-planner AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/codenameju/ai-product-planner/agents-md/github.svg)](https://agentmods.dev/instructions/codenameju/ai-product-planner/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/codenameju/ai-product-planner/agents-md"><img src="https://agentmods.dev/badge/instructions/codenameju/ai-product-planner/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ai-product-planner AGENTS.md

Your own site · 80×15
<a href="https://agentmods.dev/instructions/codenameju/ai-product-planner/agents-md"><img src="https://agentmods.dev/badge/instructions/codenameju/ai-product-planner/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 100 This file is loaded in full into every session.
When invoked 100 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00100 $0.00100
Opus 5.5 $0.00040 $0.00040
Sonnet 5.5 $0.00020 $0.00020
Haiku 4.5 $0.00010 $0.00010

Measured 2mo ago against content hash 6b0064798f46, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ai-product-planner 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 2mo 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 · 9 lines

What it actually says

Coding Agent Contract

  • Restore root causes; do not add fake-success or hardcoded AI fallbacks.
  • Run npm test, npm run lint, npm run typecheck, and npm run build after changes.
  • Keep secrets in environment variables. Never commit .env or .data.
  • Keep Planner provider-neutral through the OpenAI-compatible chat completions contract.
  • Preserve the supervisor -> parallel workers -> integration flow.
  • Public API changes require tests and README updates.
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. 2mo ago First seen · 9 lines · 100 tokens per session scan A 6b0064798f46

Subscribe to this mod's changes

ai-product-planner AGENTS.md is an instructions file published in the GitHub repository codenameju/ai-product-planner (0 stars, last pushed 3mo ago), licensed MIT. It adds 100 tokens to every session, about $0.0004 per session on Opus 5.5. 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.

Design and UXPlanning
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ai-product-planner AGENTS.mdcodenameju/ai-product-plannerInstructions file03mo agoMITA100Codex, OpenCode
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deepseek-harness AGENTS.mddeepseek-ai/deepseek-harnessInstructions file274k2d agoMITA4,313Codex, OpenCode