openai-codex-exec-plan AGENTS.md

Project instructions for using beads and execution plans in openai-codex-exec-plan, including test-driven development, where tests are written before implementation.

In plain words
What is it for?
Use them when starting work in the repository, creating an execution plan, or following its test-driven development process.
Why use it?
They define the project workflow so coding work is planned, tracked, and checked in the expected way.

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/ninjaa/openai-codex-exec-plan/agents-md
Clone the repo
git clone --depth 1 https://github.com/ninjaa/openai-codex-exec-plan

Made for: Codex, OpenCode.

Per session 1,063 This file is loaded in full into every session.
When invoked 1,063 The same file — it is already loaded in full.
Security scan C 1 finding. Scan, not verified.
Origin unknown 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 $0.01063 $0.01063
Opus 5 $0.00531 $0.00531
Sonnet 5 $0.00213 $0.00213
Haiku 4.5 $0.00106 $0.00106

Measured 2d ago against content hash 9ba8e7910442, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade C, and why

openai-codex-exec-plan AGENTS.md scanned grade C with 1 finding 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.

Recursive force deletehighDestructive command

rm -rf with a variable or a broad path is one typo away from removing the wrong tree.

2. **No destructive git commands** (`reset --hard`, `clean -fd`, `rm -rf`) without explicit approval
AGENTS.md · 126 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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 · 126 lines · 1,063 tokens per session scan C 9ba8e7910442

Subscribe to this mod's changes

openai-codex-exec-plan AGENTS.md is an instructions file published in the GitHub repository ninjaa/openai-codex-exec-plan (22 stars, last pushed 7mo ago), with no licence file. It adds 1,063 tokens to every session, about $0.0053 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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