ai-intent-driven-development AGENTS.md

Project instructions for ai-intent-driven-development, covering its agents, architecture, planning, and development workflow. AGENTS.md is a file that tells coding agents how to work in a project.

In plain words
What is it for?
Use it when planning or developing in the Exadra37/ai-intent-driven-development project.
Why use it?
It gives an agent project-specific rules and context so changes follow the repository’s intended process.

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/exadra37/ai-intent-driven-development/agents-md
Clone the repo
git clone --depth 1 https://github.com/Exadra37/ai-intent-driven-development

Made for: Codex, OpenCode.

Per session 1,959 This file is loaded in full into every session.
When invoked 1,959 The same file — it is already loaded in full.
Security scan A 0 findings. 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 $0.01959 $0.01959
Opus 5 $0.00979 $0.00979
Sonnet 5 $0.00392 $0.00392
Haiku 4.5 $0.00196 $0.00196

Measured 2d ago against content hash 0f4f2718f339, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ai-intent-driven-development 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 · 113 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 · 113 lines · 1,959 tokens per session scan A 0f4f2718f339

Subscribe to this mod's changes

ai-intent-driven-development AGENTS.md is an instructions file published in the GitHub repository Exadra37/ai-intent-driven-development (40 stars, last pushed 7mo ago), with no licence file. It adds 1,959 tokens to every session, about $0.0098 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 2026-08-30.

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