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 ZekaiSuni/claude-for-legal-turkish --skill vendor-ai-reviewgit clone --depth 1 https://github.com/ZekaiSuni/claude-for-legal-turkishWrote 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/zekaisuni/claude-for-legal-turkish/vendor-ai-review)<a href="https://agentmods.dev/skills/zekaisuni/claude-for-legal-turkish/vendor-ai-review"><img src="https://agentmods.dev/badge/skills/zekaisuni/claude-for-legal-turkish/vendor-ai-review/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/zekaisuni/claude-for-legal-turkish/vendor-ai-review"><img src="https://agentmods.dev/badge/skills/zekaisuni/claude-for-legal-turkish/vendor-ai-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00084 | $0.01251 |
| Opus 5 | $0.00042 | $0.00626 |
| Sonnet 5 | $0.00017 | $0.00250 |
| Haiku 4.5 | $0.00008 | $0.00125 |
Grade A, and why
vendor-ai-review 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/vendor-ai-review (Tedarikçi AI / Copilot Sözleşme İncelemesi)
Amaç
Tedarikçilerin (özellikle SaaS hizmetlerinin) kullanım koşullarında (Terms of Service) yer alan AI ve Copilot şartlarını incelemek. Temel soru: "Müşteri (yani şirketimiz) olarak bu veriyle onların modelini eğitiyor muyuz?"
Bu skill, AI maddelerini KVKK, FSEK ve TTK (Ticari Sır) riski açısından inceler ve ilgili maddelerin redline (düzeltme) önerisini oluşturur.
İş Akışı
- Sözleşmeyi tara ve "Artificial Intelligence", "Machine Learning", "Model Training", "Data Usage", "Telemetry", "Copilot" veya "Output/Input" kelimelerini bul.
- Aşağıdaki Türkiye ve Enterprise Odaklı AI Kontrol Listesini (Checklist) uygula.
- Kırmızı çizgileri saptayıp, Hukuk Kuralları çerçevesinde (Opt-out vs. Opt-in) redline taslağını sun.
- Privacy/Data Protection birimine handoff yapılacak bir madde varsa raporla.
Türkiye Odaklı AI Kontrol Listesi
1. Model Eğitimi (Training & Machine Learning)
- Sözleşme, tedarikçinin Customer Data'yı (Kişisel Veri, Loglar, Analitik Veriler dahil) kendi modellerini veya üçüncü parti (OpenAI vb.) modelleri eğitmek için kullanılmasına (training) izin veriyor mu?
- Hedefimiz: SIFIR eğitim yetkisi (Zero training rights) veya mutlak "Opt-out" (eğitimden çıkış) hakkı vermek. Redline hedefi: "Tedarikçi, Müşteri Verilerini ve Müşteri Çıktılarını hiçbir dil modelini (LLM) veya yapay zeka aracını eğitmek amacıyla YARARLANAMAZ."
2. Girdiler ve Çıktılar (Inputs and Outputs)
- Prompt (Girdi) ve Output (Çıktı) kime ait?
- FSEK ve Sözleşme Riski: Üretilen içeriğin/kodun mülkiyeti Müşteriye devrediliyor mu? Tedarikçi, bu çıktıları başka müşterilere gösterme veya saklama hakkına sahip mi?
- Hedefimiz: Çıktıların mülkiyetinin ve teliflerinin (FSEK uyarınca devredilebilen ekonomik haklar) münhasıran şirkete ait olması.
3. KVKK ve Yurt Dışı Veri Aktarımı (KVKK m.9)
- Girdiğimiz Müşteri verileri, tedarikçi tarafından üçüncü taraf AI modellerine (örn. OpenAI API) aktarılıyor mu?
- Eğer aktarılıyorsa bu tedarikçiler "Alt-Veri İşleyen" (Sub-processor) olarak listelenmiş mi?
- Verinin işlendiği sunucular nerede (ABD, AB)? Özel Nitelikli Kişisel Veri aktarım kısıtı var mı?
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.
- 12d ago First seen · 71 lines · 84 tokens per session scan A c4f156abc562
vendor-ai-review is a skill published in the GitHub repository ZekaiSuni/claude-for-legal-turkish (103 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 84 tokens to every session and 1,251 once invoked, about $0.0004 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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