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 esaterbiltavus/yapay-zeka-turkce-dilekce-skilleri --skill dilekce-toulmingit clone --depth 1 https://github.com/esaterbiltavus/yapay-zeka-turkce-dilekce-skilleriWrote 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/esaterbiltavus/yapay-zeka-turkce-dilekce-skilleri/dilekce-toulmin)<a href="https://agentmods.dev/skills/esaterbiltavus/yapay-zeka-turkce-dilekce-skilleri/dilekce-toulmin"><img src="https://agentmods.dev/badge/skills/esaterbiltavus/yapay-zeka-turkce-dilekce-skilleri/dilekce-toulmin/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/esaterbiltavus/yapay-zeka-turkce-dilekce-skilleri/dilekce-toulmin"><img src="https://agentmods.dev/badge/skills/esaterbiltavus/yapay-zeka-turkce-dilekce-skilleri/dilekce-toulmin.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 | $0.00200 | $0.01614 |
| Opus 5 | $0.00100 | $0.00807 |
| Sonnet 5 | $0.00040 | $0.00323 |
| Haiku 4.5 | $0.00020 | $0.00161 |
Grade A, and why
dilekce-toulmin 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Toulmin Modeli ile Dilekçe Oluşturma
Toulmin Modeli, katı bir şema değil esnek bir argüman iskeletidir. Bir iddianın (Claim) hangi vakıaya (Grounds) dayandığını ve bu ikisini birbirine bağlayan örtük hukuki gerekçeyi — warrant (köprü) — açık eder. Argümanın "neden geçerli olduğunu" görünür kıldığı için, karşı tarafın argümanındaki zayıf veya eksik köprüyü hedeflemekte güçlüdür.
Ne zaman kullanılır
- Karşı tarafın argümanındaki zayıf halkayı (eksik/yanlış warrant) görünür kılmak gerekiyor.
- İtiraz dilekçesi, bilirkişi raporuna itiraz veya red talebi yazılacak.
- Vakıa ile talep arasındaki hukuki köprünün (warrant) ayrıca ve açıkça gösterilmesi isteniyor.
- Dava, cevap, replik, düplik veya ceza savunması — tür fark etmez.
Toulmin mantığı
- Claim — İddia: Mahkemeden istenen sonuç; ulaşılmak istenen talep/nitelendirme.
- Grounds — Dayanak: İddiayı taşıyan maddi vakıa ve deliller.
- Warrant — Gerekçe/Köprü: Vakıayı (Grounds) iddiaya (Claim) bağlayan örtük hukuki gerekçe; işin kalbi.
- Backing — Destek: Warrant'ın kendisini ayakta tutan dayanak (mevzuat/içtihat/ilke).
- Qualifier — Çekince: İddianın kesinlik derecesi ("kural olarak", "büyük olasılıkla").
- Rebuttal — Çürütme: Karşı tarafın warrant'ını/argümanını hedefleyen karşı değerlendirme.
Çalışma akışı
- Dilekçe türünü belirle (dava/cevap/replik/düplik/savunma) —
references/bicim-ve-cikti.md. - Bilgileri topla: mahkeme ve dosya no, taraflar, konu, talepler, vakıalar, deliller.
Eksikleri
AskUserQuestionveya kısa sorularla tamamla. Dava dosyası verildiyse oku:.udf→udf-cli udf2md; çok sayfalı.tiff/.tif→ sayfalara böl, tek tek oku; PDF/foto/metin → doğrudan oku. - Toulmin iskeletini kur — her iddia için Claim–Grounds–Warrant–Backing–Qualifier–Rebuttal
unsurlarını çıkar; adım tanımları ve eşleme tablosu için
references/cerceve-yapisi.md. - Gövdeyi yaz: AÇIKLAMALAR'ı
Claim → Grounds → Warrant → Backing → Qualifier → Rebuttalakışıyla kur. Warrant'ı (vakıayı talebe bağlayan köprü) ayrıca ve açıkça göster; karşı tarafın argümanını çürütürken doğrudan onun warrant'ını hedefle. - Çıktıyı üret (docx/html/udf/pdf) —
references/bicim-ve-cikti.md. - Doğrula ve sun.
What ships with it
2 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.
- 12d ago First seen · 85 lines · 200 tokens per session scan A 678c28c86c69
dilekce-toulmin is a skill published in the GitHub repository esaterbiltavus/yapay-zeka-turkce-dilekce-skilleri (12 stars, last pushed 2mo ago), licensed MIT. It adds 200 tokens to every session and 1,614 once invoked, about $0.0010 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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