Borrowing it
Nothing to install: this file belongs to geekfujiwara/CodeAppsDevelopmentStandard. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/geekfujiwara/CodeAppsDevelopmentStandard/main/.github/skills/ai-builder/SKILL.mdgit clone --depth 1 https://github.com/geekfujiwara/CodeAppsDevelopmentStandardWrote 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/geekfujiwara/codeappsdevelopmentstandard/ai-builder)<a href="https://agentmods.dev/skills/geekfujiwara/codeappsdevelopmentstandard/ai-builder"><img src="https://agentmods.dev/badge/skills/geekfujiwara/codeappsdevelopmentstandard/ai-builder/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/geekfujiwara/codeappsdevelopmentstandard/ai-builder"><img src="https://agentmods.dev/badge/skills/geekfujiwara/codeappsdevelopmentstandard/ai-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 368 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 374 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Data Exfiltration · line 99 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00060 | $0.04677 |
| Opus 5.5 | $0.00024 | $0.01871 |
| Sonnet 5.5 | $0.00012 | $0.00935 |
| Haiku 4.5 | $0.00006 | $0.00468 |
Grade A, and why
ai-builder scanned grade A 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
r = requests.post( How it starts
The opening of the file, as written. The whole thing — 401 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Builder AI プロンプト構築スキル
AI Builder の AI プロンプト(GPT Dynamic Prompt) を Dataverse API で作成し、 Copilot Studio エージェントに ツール(アクション) として追加する。 Power Automate フローから aibuilderpredict_customprompt で呼び出すパターンも含む。
基本方針: AI プロンプトを常にプレビルトモデルより優先する
AI Builder で AI 処理を実装する場合、以下の方針に従う:
✅ AI プロンプト(カスタムプロンプト)を常に第一選択肢とする
- 請求書処理、ドキュメント情報抽出、分類、要約 等すべて
- プロンプトテキスト + document/image 入力で柔軟に対応
- トレーニングデータ不要、即座にデプロイ・更新可能
- プロンプト変更だけで出力形式・抽出項目を自由に調整
❌ プレビルトモデル(請求書処理モデル等)は原則使用しない
- 従来型のプレビルトモデルやカスタムモデルはトレーニング(学習)が必要
- AI プロンプトで同等の処理がプロンプトだけで実現できる
⚠ プレビルトモデルを使う例外ケース(稀)
- 手書き文字の高精度 OCR が必須で AI プロンプトでは精度不足の場合
- 既存のプレビルトモデルが組み込まれたワークフローを維持する必要がある場合
前提: 設計フェーズ完了後に構築に入る(必須)
AI プロンプトを構築する前に、プロンプト設計をユーザーに提示し承認を得ていること。
設計提示時に含める内容:
| 項目 | 内容 |
|---|---|
| プロンプト名 | 英語推奨(スキーマ名に使用される) |
| プロンプトテキスト | リテラルテキスト+入力変数の組み合わせ |
| 入力変数 | 名前・型(text / document / image)・説明・テスト値 |
| 出力形式 | text or json(JSON の場合はスキーマ+サンプル) |
| モデルパラメータ | モデル種別(gpt-41-mini 等)・temperature |
| 利用先 | Copilot Studio ツール or Power Automate フロー |
| shouldPromptUser | 各入力変数をユーザーに自動的に尋ねるか(true/false) |
事前確認(会話の最初に 1 回だけ)
本スキルの利用が確定したら、standard の共通契約に加え、 1 回の AskUserQuestion で次をまとめて確認する。
| # | 質問 | 合格条件 |
|---|---|---|
| 1 | 対象環境で AI Builder を利用できるか | 必要なライセンス / AI Builder capacity があり、利用制限を確認している |
| 2 | AI プロンプトを作成・公開する権限があるか | msdyn_aimodel 等の必要テーブルと AIModelPublish を実行できる担当者がいる |
| 3 | 利用先はどこか | Copilot Studio / Power Automate、接続参照、実行ユーザー、呼び出し側ライセンスを確定している |
| 4 | 入力データをモデルへ送信してよいか | document / image / text の分類、個人情報、保持・リージョン要件を承認済みである |
| 5 | プロンプト、入力、JSON schema、モデル、テスト値は承認済みか | 正常系、拒否すべき入力、期待出力を記録している |
System Administrator を常用せず、AI モデルの作成・公開とソリューション追加に必要な
Dataverse 権限だけを持つ担当者を優先する。capacity または権限が未確認なら
AIModelPublish を呼び出さない。
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago Changed · +17 lines 535f170f92e5
- 2mo ago First seen · 384 lines · 60 tokens per session scan A 6f6539d4ef7c
ai-builder is a skill published in the GitHub repository geekfujiwara/CodeAppsDevelopmentStandard (78 stars, last pushed yesterday), licensed MIT. It adds 60 tokens to every session and 4,677 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
ai-builder compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| ai-buildergeekfujiwara/CodeAppsDevelopmentStandard | Skill | 78 | yesterday | MIT | A | 60 | Claude Code, Codex |
| llm-app-patternsdavila7/claude-code-templates | Skill | 33k | yesterday | MIT | A | 54 | Claude Code, Codex |
| prompt-engineerJeffallan/claude-skills | Skill | 12k | 7d ago | MIT | A | 93 | Claude Code |
| prompt-optimizationlangwatch/langwatch | Skill | 5.0k | yesterday | Apache-2.0 | A | 105 | Claude Code, Codex |
| omh-model-optimizationrlaope/oh-my-hermes | Skill | 5.2k | today | MIT | A | 84 | Claude Code, Codex |
| ideogram4digitalsamba/claude-code-video-toolkit | Skill | 2.5k | today | MIT | A | 99 | Claude Code |
| prompt-library-for-startupsaws/agent-toolkit-for-aws | Skill | 3.4k | yesterday | Apache-2.0 | A | 228 | Claude Code |