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 agentmods add skills/fthsrbst/mnema/learnnpx skills add fthsrbst/mnema --skill learngit clone --depth 1 https://github.com/fthsrbst/mnemaWrote 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/fthsrbst/mnema/learn)<a href="https://agentmods.dev/skills/fthsrbst/mnema/learn"><img src="https://agentmods.dev/badge/skills/fthsrbst/mnema/learn.svg" alt="Measured on agentmods" 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 | $0.00077 | $0.00551 |
| Opus 5 | $0.00039 | $0.00275 |
| Sonnet 5 | $0.00015 | $0.00110 |
| Haiku 4.5 | $0.00008 | $0.00055 |
Grade A, and why
learn 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 4d 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.
What it actually says
Learn — Öğrenme Akışı
Amaç: öğrenilen her konu aranabilir, tekrar edilebilir kalıcı bilgiye dönüşsün.
Akış
- Seviye tespiti:
memory_search("<konu>")+rag_search("<konu>")— daha önce bu konuda not var mı? Varsa üstüne inşa et, sıfırdan anlatma. - Katmanlı anlatım:
- Önce zihinsel model (bu ne, hangi sorunu çözüyor, neye benziyor)
- Sonra çalışan minimal kod örneği (kullanıcının bildiği stack'te)
- Sonra "gerçek hayatta nerede kırılır" (yaygın hatalar, edge case'ler)
- Uygulatma: küçük bir egzersiz öner; kullanıcı kodu yazsın, sen review et. İzlemek değil yapmak öğretir.
- Not üret ve indeksle: konu kapanırken kompakt bir öğrenme notu yaz ve
rag_addile kaydet:title: "Öğrenme notu: <konu>" uri: "learn/<konu-slug>" ← tekrar öğrenmede re-index olur project: "learning" text: # <Konu> ## Zihinsel model (2-3 cümle) ## Temel API/kavramlar (madde madde) ## Kod örneği (çalışan, minimal) ## Tuzaklar (yaşanan hatalar dahil) ## Açık sorular (henüz anlaşılmayanlar) - Mini quiz: 3-4 soru sor (kod okuma + "bu neden patlar?" tarzı). Yanlışları nota işle.
Tekrar (spaced repetition)
Kullanıcı "tekrar edelim" derse: rag_search(project="learning") ile eski notları çek, "Açık sorular" bölümlerinden ve tuzaklardan quiz üret. Doğru cevaplananları nottan düşür, notu rag_add ile (aynı uri) güncelle.
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.
- 4d ago First seen · 34 lines · 77 tokens per session scan A 7e9d2a331bf7
learn is a skill published in the GitHub repository fthsrbst/mnema (2 stars, last pushed 4d ago), licensed MIT. It adds 77 tokens to every session and 551 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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