marketing-claims-review

marketing-claims-review is a skill for Claude Code from ZekaiSuni/claude-for-legal-turkish. It costs 73 tokens per session (1,055 once invoked), scanned A, original, Apache-2.0.

A review skill for checking advertising and marketing claims under Turkish advertising law. It covers landing pages, emails, social posts, app-store text, discounts, campaigns, influencers, and testimonials.

In plain words
What is it for?
It extracts factual, comparative, absolute, implied, pricing, influencer, testimonial, and sensitive-sector claims, then reports evidence requirements and suggested rewrites.
Why use it?
It identifies claims that may need proof, clearer wording, disclaimers, or changes before publication. This helps reduce the risk of misleading advertising or breaking sector-specific rules.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Part of the product-legal plugin — 4 skills, 1 agent shipped together

Good fit It extracts factual, comparative, absolute, implied, pricing, influencer, testimonial, and sensitive-sector claims, then reports evidence requirements and suggested rewrites.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zekaisuni/claude-for-legal-turkish/marketing-claims-review
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.

Any agent
npx skills add ZekaiSuni/claude-for-legal-turkish --skill marketing-claims-review
Clone the repo
git clone --depth 1 https://github.com/ZekaiSuni/claude-for-legal-turkish

Made for: Claude Code.

Or install product-legal, the plugin that ships this one along with the rest of its 4 skills, 1 agent.

Wrote 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.

agentmods badge for marketing-claims-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/zekaisuni/claude-for-legal-turkish/marketing-claims-review/github.svg)](https://agentmods.dev/skills/zekaisuni/claude-for-legal-turkish/marketing-claims-review)
Your own site
<a href="https://agentmods.dev/skills/zekaisuni/claude-for-legal-turkish/marketing-claims-review"><img src="https://agentmods.dev/badge/skills/zekaisuni/claude-for-legal-turkish/marketing-claims-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.

agentmods 80×15 button for marketing-claims-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/zekaisuni/claude-for-legal-turkish/marketing-claims-review"><img src="https://agentmods.dev/badge/skills/zekaisuni/claude-for-legal-turkish/marketing-claims-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,055 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00073 $0.01055
Opus 5 $0.00036 $0.00528
Sonnet 5 $0.00015 $0.00211
Haiku 4.5 $0.00007 $0.00105

Measured 9d ago against content hash 58e9b060e068, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

marketing-claims-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 9d 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.

product-legal/skills/marketing-claims-review/SKILL.md · 89 lines

How it starts

The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/marketing-claims-review

Amac

Pazarlama metnindeki olculebilir, karsilastirmali, mutlak, ima edilen veya hassas sektor iddialarini bul; kanit gereksinimini ve duzeltme onerilerini ver. Reklam Kurulu/Ticaret Bakanligi, 6502 ve ilgili sektor kurallari guncel kaynak kontrolu gerektirebilir.

Akis

  1. Product profile ## Pazarlama Iddialari bolumunu oku.
  2. Asset'i oku: metin, gorsel ima, fiyat/indirim, influencer/testimonial, mecra ve hedef kitle.
  3. Her iddiayi ayikla; saf subjektif ifade disinda kalanlari tabloya al.
  4. Iddia tipini belirle: olgusal, karsilastirmali, ima edilen, mutlak, fiyat/indirim, influencer/testimonial, sektor hassas.
  5. Kanit dosyasi, metodoloji, tarih, kapsam ve disclaimers kontrolu yap.
  6. Kisa asset'lerde duzeltilmis metni dogrudan yaz; uzun asset'lerde degisiklik listesini ver.

Turk Reklam Kontrol Kapilari

  • Reklam dogru, durust, kamu duzeni/genel ahlak ve kisilik haklarina uygun mu?
  • Tuketici deneyim/bilgi eksikligi istismar ediliyor mu?
  • Ortulu reklam veya ifsasiz influencer/testimonial var mi?
  • Karsilastirmali reklamda rakip marka/logo/unvan kullaniliyor mu; karsilastirma objektif, olculebilir, dogrulanabilir mi?
  • Indirimde onceki fiyat, baslangic/bitis tarihi ve stok/miktar siniri acik mi?
  • "Ucretsiz", "garantili", "sinirsiz", "en iyi", "tek", "100%", "risksiz" gibi mutlak ifadeler kanitlanabilir mi?
  • Saglik, gida, takviye edici gida, kozmetik, finans, cocuk, oyun veya regule sektor iddiasi var mi?
  • Platform politikasi veya mecra kurali canli dogrulama gerektiriyor mu?

Iddia Tablolama

**Iddia:** "[tam alinti]"
**Tip:** [Olgusal | Karsilastirmali | Ima edilen | Mutlak | Fiyat/indirim | Influencer/testimonial | Sektor hassas]
**Kanit dosyasi:** [Var - kaynak | Yok | Bilinmiyor]
**Cagri:** [Temiz | Kanit gerekir | Yeniden yaz | Kes]
**Onerilen metin:** "[alternatif]"
**Neden:** [tek cumle]
**Dogrulama:** [Ticaret Bakanligi/Reklam Kurulu/KVKK/platform/kullanici sagladi/dogrula]

Cikti

[GIZLI HUKUKI / URUN HUKUKU CALISMA TASLAGI - HUKUKCU INCELEMESINE TABIDIR]

Reviewer note
- Kaynaklar:
- Okuma kapsami:
- Dogrulanmasi gerekenler:
- Aksiyon oncesi:

# Reklam Iddia Incelemesi: [Asset]

## Ozet

[N] iddia incelendi. [N] temiz, [N] kanit/duzeltme, [N] kes.

**Yayin durumu:** [Yayinlanabilir | Degisiklikle yayinlanabilir | Yayinlanmamali]

## Iddia Bazli Inceleme

[Kirmizi once, sonra sari, sonra temiz]

## Onerilen Revizyon

[Kisa metinlerde final revize metin; uzun metinlerde degisiklik listesi]

## Yayin Oncesi Gereken Kanitlar

| Iddia | Gereken kanit | Sahip |
|---|---|---|

Read the full file on GitHub · 89 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. 9d ago First seen · 89 lines · 73 tokens per session scan A 58e9b060e068

Subscribe to this mod's changes

marketing-claims-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 73 tokens to every session and 1,055 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 2026-09-03.

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