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.
npx skills add mturac/everything-openai-codex --skill ai-first-engineeringgit clone --depth 1 https://github.com/mturac/everything-openai-codexWrote 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.
[](https://agentmods.dev/skills/mturac/everything-openai-codex/ai-first-engineering)<a href="https://agentmods.dev/skills/mturac/everything-openai-codex/ai-first-engineering"><img src="https://agentmods.dev/badge/skills/mturac/everything-openai-codex/ai-first-engineering/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.
<a href="https://agentmods.dev/skills/mturac/everything-openai-codex/ai-first-engineering"><img src="https://agentmods.dev/badge/skills/mturac/everything-openai-codex/ai-first-engineering.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00035 | $0.00493 |
| Opus 5 | $0.00017 | $0.00246 |
| Sonnet 5 | $0.00007 | $0.00099 |
| Haiku 4.5 | $0.00003 | $0.00049 |
Grade A, and why
ai-first-engineering 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.
What it actually says
AI ファーストエンジニアリング
AI 支援コード生成でリリースするチームのプロセス、レビュー、アーキテクチャを設計する際にこのスキルを使用します。
プロセスの変化
- 計画の品質はタイピングスピードより重要。
- 評価のカバレッジは個人的な自信より重要。
- レビューの焦点は構文からシステムの動作へ。
アーキテクチャ要件
エージェントフレンドリーなアーキテクチャを優先する：
- 明示的な境界
- 安定したコントラクト
- 型付きインターフェース
- 決定論的なテスト
隠れた慣習に広がる暗黙の動作を避ける。
AI ファーストチームでのコードレビュー
レビュー対象：
- 動作のリグレッション
- セキュリティの前提
- データの整合性
- 障害処理
- ロールアウトの安全性
自動化によって既にカバーされているスタイルの問題に費やす時間を最小化する。
採用と評価シグナル
AI ファーストの強いエンジニア：
- 曖昧な作業を明確に分解する
- 測定可能な受け入れ基準を定義する
- 高シグナルのプロンプトと評価を生成する
- 納期プレッシャー下でリスクコントロールを強制する
テスト標準
生成されたコードのテストバーを引き上げる：
- 操作されたドメインに対する必須のリグレッションカバレッジ
- 明示的なエッジケースのアサーション
- インターフェース境界の統合チェック
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.
- 5d ago First seen · 52 lines · 35 tokens per session scan A 2e5902ce2d88
ai-first-engineering is a skill published in the GitHub repository mturac/everything-openai-codex (89 stars, last pushed 15d ago), licensed MIT. It adds 35 tokens to every session and 493 once invoked, about $0.0002 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 2026-09-03.
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