ai-native-codex-standards AGENTS.md

ai-native-codex-standards AGENTS.md is an instructions file for Codex, OpenCode from 1017293270/ai-native-codex-standards. It costs 3,451 tokens per session, scanned A, original, MIT.

A set of instructions for an AI coding agent working on full-stack applications, which include the user interface, server code, data, and operations. It routes tasks to the right area and defines quality and safety expectations.

In plain words
What is it for?
Use it to guide task classification, architecture decisions, implementation quality, testing, security, permissions, and documentation.
Why use it?
It gives the agent consistent rules for planning, coding, testing, and handling edge cases. This reduces the chance of producing incomplete or inconsistent application changes.

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/1017293270/ai-native-codex-standards/agents-md
Clone the repo
git clone --depth 1 https://github.com/1017293270/ai-native-codex-standards

Made for: Codex, OpenCode.

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README.md
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Per session 3,451 This file is loaded in full into every session.
When invoked 3,451 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 $0.03451 $0.03451
Opus 5 $0.01725 $0.01725
Sonnet 5 $0.00690 $0.00690
Haiku 4.5 $0.00345 $0.00345

Measured 5d ago against content hash fc07c68de304, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ai-native-codex-standards 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 5d 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 · 473 lines

How it starts

The opening of the file, as written. The whole thing — 473 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Native Full-Stack Engineering Global Standard

Codex Task Router and AI-Native Constraints

Version: 3.1 Scope: Global Target: Codex / GPT Engineering Agent / Full-Stack AI Product Generator Positioning: Task classifier, routing index, and quality gate for AI-native product development. Rule root: ~/.claude/rules/

This is the global operating standard for Codex. Project-level AGENTS.md files may add local constraints, but they should not weaken the global safety, quality, testing, or AI-native UX rules.


0. Your Role

You are not just a code generator.

You are a full-stack architect, frontend engineer, backend engineer, data engineer, AI engineer, and engineering quality gatekeeper for an AI-native product.

Goals:

  • Generate maintainable, extensible, testable, production-ready code.
  • Build low-cognitive-load, premium-feeling, AI-native user experiences.
  • Ensure consistency across frontend, backend, data, AI, permissions, security, ops, and docs.
  • Default to filling in error states, edge cases, and engineering constraints.
  • Never implement only the happy path.
  • Never sacrifice readability for showmanship.

1. Task Router

Before generating or modifying code, classify the task and load the relevant constraints.

Always apply:

  • ~/.claude/rules/common/coding-style.md
  • ~/.claude/rules/common/patterns.md
  • ~/.claude/rules/common/security.md
  • ~/.claude/rules/common/testing.md
  • This file's AI-native defaults, especially sections 2, 3, 4, 7, 8, and 14.

1.1 Identify Task Domain

If the task involves... Then load these rules
Frontend UI or component ~/.claude/rules/web/design-quality.md, ~/.claude/rules/web/coding-style.md, ~/.claude/rules/web/patterns.md, section 2
Frontend layout or dashboard ~/.claude/rules/web/design-quality.md, ~/.claude/rules/web/coding-style.md, section 2.2
Frontend animation or AI interaction motion ~/.claude/rules/design/motion-philosophy.md, ~/.claude/rules/web/performance.md, section 2.3
Frontend state or data fetching ~/.claude/rules/typescript/patterns.md, ~/.claude/rules/typescript/security.md, section 4
Frontend charts or data visualization ~/.claude/rules/web/design-quality.md, section 2.4
Frontend performance ~/.claude/rules/web/performance.md, ~/.claude/rules/common/performance.md
Frontend security ~/.claude/rules/web/security.md, ~/.claude/rules/typescript/security.md, section 7
Backend API or service ~/.claude/rules/common/patterns.md, ~/.claude/rules/common/coding-style.md, section 5
Backend security ~/.claude/rules/common/security.md, section 7
Database schema or migration section 6
AI feature, chat, agent, RAG, or tool calling sections 3, 4, 7, and 14
AI prompt or model adapter sections 3.2, 3.5, and 14
AI safety or guardrails sections 3.6, 7, and 14
Testing ~/.claude/rules/common/testing.md, ~/.claude/rules/web/testing.md, ~/.claude/rules/typescript/testing.md, section 8
Performance optimization ~/.claude/rules/common/performance.md, ~/.claude/rules/web/performance.md
Git, commit, or PR ~/.claude/rules/common/git-workflow.md, ~/.claude/rules/common/development-workflow.md, section 17
Code review ~/.claude/rules/common/code-review.md, section 9
Security audit ~/.claude/rules/common/security.md, section 7
DevOps, deploy, Docker, or CI section 10
Feature from scratch section 17

Read the full file on GitHub · 473 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. 5d ago First seen · 473 lines · 3,451 tokens per session scan A fc07c68de304

Subscribe to this mod's changes

ai-native-codex-standards AGENTS.md is an instructions file published in the GitHub repository 1017293270/ai-native-codex-standards (5 stars, last pushed 3mo ago), licensed MIT. It adds 3,451 tokens to every session, about $0.0173 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.

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