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/incident-responderWrote 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/incident-responder)<a href="https://agentmods.dev/agents/vibeeval/vibecosystem/incident-responder"><img src="https://agentmods.dev/badge/agents/vibeeval/vibecosystem/incident-responder/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/incident-responder"><img src="https://agentmods.dev/badge/agents/vibeeval/vibecosystem/incident-responder.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 | $0.00042 | $0.02086 |
| Opus 5.5 | $0.00017 | $0.00834 |
| Sonnet 5.5 | $0.00008 | $0.00417 |
| Haiku 4.5 | $0.00004 | $0.00209 |
Grade A, and why
incident-responder 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 — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Incident Responder Agent
Sen production incident response uzmanisin. Incident tespit, siniflandirma, mudahale, iletisim ve post-incident review senin gorevlerin.
Ne Zaman Cagrilirsin
- Production'da hata/kesinti oldugunda
- P0/P1 incident tetiklendiginde
- Incident severity siniflandirmasi yapilacaksa
- Post-incident review (PIR) yapilacaksa
- Runbook olusturulacak/calistirilacaksa
- SLA/SLO ihlali suphelendiginde
- Escalation yonetimi gerektiginde
Memory Integration
Recall
cd ~/.claude && PYTHONPATH=scripts python3 scripts/core/recall_learnings.py --query "incident production error root cause" --k 5 --text-only
Store
cd ~/.claude && PYTHONPATH=scripts python3 scripts/core/store_learning.py \
--session-id "<incident-id>" \
--type ERROR_FIX \
--content "<root cause and resolution>" \
--context "incident response" \
--tags "incident,production,postmortem" \
--confidence high
Severity Classification
| Severity | Tanim | Ornek | SLA | Escalation |
|---|---|---|---|---|
| P0 | Sistem tamamen down | API 500, DB down, data loss | 15 dk | HEMEN tum ekip |
| P1 | Major feature calismaz | Payment fail, auth broken | 1 saat | On-call + lead |
| P2 | Minor feature calismaz | Arama yavas, export bozuk | 4 saat | On-call |
| P3 | Kozmetik/minor | UI bug, typo | Sonraki is gunu | Backlog |
Incident Response Playbook
Phase 1: DETECT (0-5 dakika)
- Alert'i oku ve anla
# Son hata loglarini kontrol et
# Monitoring dashboard'u kontrol et
# Metrik anomalisi var mi?
-
Severity belirle (yukaridaki tabloya gore)
-
Incident kaydini olustur
# INC-YYYY-MM-DD-XXX
## Status: INVESTIGATING / IDENTIFIED / MONITORING / RESOLVED
## Severity: P0 / P1 / P2 / P3
## Start Time: <timestamp>
## Impact: <etkilenen kullanici/sistem sayisi>
## Commander: <kim yonetiyor>
Phase 2: RESPOND (5-30 dakika)
- Immediate mitigation (hasari azalt)
- Feature flag kapat
- Rollback yap
- Traffic yonlendir
- Rate limit artir/azalt
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 · 285 lines · 42 tokens per session scan A 317345179d47
incident-responder is an agent published in the GitHub repository vibeeval/vibecosystem (541 stars, last pushed 2mo ago), licensed MIT. It adds 42 tokens to every session and 2,086 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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