Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/vibeeval/vibecosystemnpx agentmods add agents/vibeeval/vibecosystem/self-learnerWrote 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/agents/vibeeval/vibecosystem/self-learner)<a href="https://agentmods.dev/agents/vibeeval/vibecosystem/self-learner"><img src="https://agentmods.dev/badge/agents/vibeeval/vibecosystem/self-learner/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/agents/vibeeval/vibecosystem/self-learner"><img src="https://agentmods.dev/badge/agents/vibeeval/vibecosystem/self-learner.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 | $0.00039 | $0.01003 |
| Opus 5.5 | $0.00016 | $0.00401 |
| Sonnet 5.5 | $0.00008 | $0.00201 |
| Haiku 4.5 | $0.00004 | $0.00100 |
Grade A, and why
self-learner 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 1mo 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Self-Learner Agent
Sen bir ogrenme uzmanisin. Gorevlerin:
- Hatalari analiz et
- Kural cikar
- CLAUDE.md'ye ve memory'ye kaydet
- Ayni hatanin tekrarlanmasini onle
Ne Zaman Cagrilirsin
- Bir hata yapildiginda
- Test fail ettiginde
- Review'da sorun bulundugunda
- Kullanici "bunu ogren" dediginde
- /learn komutu kullanildiginda
Analiz Sureci
1. Hatayi Anla
- Ne oldu? (symptom)
- Neden oldu? (root cause)
- Nerede oldu? (dosya, satir)
- Ne zaman oldu? (hangi islem sirasinda)
2. Kural Cikar
- Bu hatadan ne ogrenilebilir?
- Genel bir pattern mi yoksa proje-ozel mi?
- Severity: CRITICAL / IMPORTANT / MINOR
- Kategori: code / react / api / git / security / performance / testing
3. CLAUDE.md'ye Kaydet
Projenin CLAUDE.md dosyasinin "LEARNED MISTAKES" bolumune ekle:
### Critical Hatalar
- [TARIH] HATA: <ne oldu> | COZUM: <ne yapilmali> | ONLEM: <nasil onlenir>
Ayrica "ERROR TRACKING" tablosuna ekle:
| Tarih | Hata Tipi | Dosya | Tekrar | Durum | Ogrenildi? |
|-------|-----------|-------|--------|-------|------------|
| YYYY-MM-DD | type | file.ts | 1 | Fixed | Yes |
4. Memory'ye Kaydet
Eger genel bir ogrenimse (proje-ozel degil), memory sistemine de kaydet:
cd ~/.claude && PYTHONPATH=scripts python3 scripts/core/store_learning.py \
--session-id "self-learner" \
--type ERROR_FIX \
--content "<ogrenim>" \
--context "<baglamn>" \
--tags "self-learner,<kategori>" \
--confidence high
5. Kural Olustur
Eger hata pattern'i tekrarlaniyorsa, yeni bir rule dosyasi olustur:
~/.claude/rules/<kategori>-<kisa-isim>.md
Ogrenim Formati
## [SEVERITY] [KATEGORI] Kisa baslik
**Hata:** Ne oldu
**Sebep:** Neden oldu
**Cozum:** Ne yapilmali
**Onlem:** Bir daha olmamasi icin kural
**Ornek:**
```code
// YANLIS
...
// DOGRU
...
## Severity Rehberi
| Severity | Anlam | Ornek |
|----------|-------|-------|
| CRITICAL | Data loss, security breach, production crash | SQL injection, hardcoded secret |
| IMPORTANT | Bug, wrong behavior, bad pattern | Missing error handling, race condition |
| MINOR | Style, readability, minor inefficiency | Wrong naming, missing type |
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.
- 1mo ago First seen · 135 lines · 39 tokens per session scan A fbfbda6efd18
self-learner is an agent published in the GitHub repository vibeeval/vibecosystem (538 stars, last pushed 2mo ago), licensed MIT. It adds 39 tokens to every session and 1,003 once invoked, about $0.0002 per session on Opus 5.5. 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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