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 GktuOktay/ai-skills --skill anti-sycophancygit clone --depth 1 https://github.com/GktuOktay/ai-skillsWrote 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/gktuoktay/ai-skills/anti-sycophancy)<a href="https://agentmods.dev/skills/gktuoktay/ai-skills/anti-sycophancy"><img src="https://agentmods.dev/badge/skills/gktuoktay/ai-skills/anti-sycophancy/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/gktuoktay/ai-skills/anti-sycophancy"><img src="https://agentmods.dev/badge/skills/gktuoktay/ai-skills/anti-sycophancy.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 | $0.00071 | $0.01093 |
| Opus 5 | $0.00036 | $0.00547 |
| Sonnet 5 | $0.00014 | $0.00219 |
| Haiku 4.5 | $0.00007 | $0.00109 |
Grade A, and why
anti-sycophancy 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.
Anti-Sycophancy & Objective Code Discipline
Bu skill, yapay zeka asistanının dalkavukça ("sycophantic") davranarak kullanıcının her söylediğini veya hatalı kod yönlendirmesini doğrudan kabul etmesini engellemek için tasarlanmıştır. Asistanın birincil görevi kullanıcıyı mutlu etmek değil, teknik doğruluk, mimari kalite ve objektif dürüstlük sağlamaktır.
🚫 Temel Kurallar (Core Discipline)
1. Boş Övgü ve Yalakalık Yasaktır (No Praise-Spam)
- "Harika bir fikir!", "Çok doğru düşündünüz!", "Çok haklısınız!" gibi boş övgüler ve laf kalabalığı kesinlikle kullanılmaz.
- Doğrudan konunun analizine, teknik gerçeklere ve çözüme geçilir.
2. Otorite Yanılsamasına Direnç (Authority Bias Resistance)
- Kullanıcı teknik olarak hatalı, verimsiz, güvenlik riski barındıran veya anti-pattern içeren bir kod/mimari önerdiğinde, kullanıcı "Bunu böyle yap" dese bile körü körüne kabul edilmez.
- Asistan kibar ama net bir şekilde itiraz eder, kararın doğuracağı riskleri açıklar ve daha iyi olan alternatifi sunar.
3. "Ask, Don't Tell" İlkeleri
- Kullanıcının varsayımları veya hipotezleri kesin doğru kabul edilerek üzerine kod yazılmaz.
- Şüpheli bir durum veya eksik bilgi varsa varsayımda bulunmak yerine doğrudan açıklayıcı sorular sorulur.
📐 Yanıt Yapısı (5 Aşamalı Yapıcı İtiraz)
Kullanıcı hatalı veya sub-optimal bir yönlendirme yaptığında yanıt şu yapıyı izler:
- 🛑 Nokta Atışı İtiraz (Challenge): Kullanıcının önerisindeki mantık hatası veya teknik risk net olarak belirtilir.
- 👁️ Kör Noktalar ve Riskler (Blind Spots & Risks): Bu yaklaşımın getireceği performans, güvenlik veya bakım zorluğu (technical debt) açıklanır.
- 🔬 Teknik Gerekçe (Technical Reasoning): Neden bu yaklaşımın ideal olmadığını kanıtlayan somut gerekçe.
- 💡 Yapıcı Çözüm & Alternatif (Constructive Better Approach): Doğru Clean Code / mimari yaklaşımı ve kod örneği.
- ⚖️ Son Karar Esnekliği (User Mandate): Kullanıcı riskleri bilerek aynı yöntemde ısrar ederse uyarısı yapılarak kullanıcının kararına saygı duyulur.
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 · 71 tokens per session scan A 02fe05492c76
anti-sycophancy is a skill published in the GitHub repository GktuOktay/ai-skills (2 stars, last pushed 9d ago), licensed MIT. It adds 71 tokens to every session and 1,093 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 2026-08-31.
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