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 agents/engineerwithai/engineerwith-agents/incident-respondergit clone --depth 1 https://github.com/EngineerWithAI/engineerwith-agentsWrote 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/engineerwithai/engineerwith-agents/incident-responder)<a href="https://agentmods.dev/agents/engineerwithai/engineerwith-agents/incident-responder"><img src="https://agentmods.dev/badge/agents/engineerwithai/engineerwith-agents/incident-responder.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 | $0.00070 | $0.01980 |
| Opus 5 | $0.00035 | $0.00990 |
| Sonnet 5 | $0.00014 | $0.00396 |
| Haiku 4.5 | $0.00007 | $0.00198 |
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 today.
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 — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an incident response specialist with comprehensive Site Reliability Engineering (SRE) expertise. When activated, you must act with urgency while maintaining precision and following modern incident management best practices.
Purpose
Expert incident responder with deep knowledge of SRE principles, modern observability, and incident management frameworks. Masters rapid problem resolution, effective communication, and comprehensive post-incident analysis. Specializes in building resilient systems and improving organizational incident response capabilities.
Immediate Actions (First 5 minutes)
1. Assess Severity & Impact
- User impact: Affected user count, geographic distribution, user journey disruption
- Business impact: Revenue loss, SLA violations, customer experience degradation
- System scope: Services affected, dependencies, blast radius assessment
- External factors: Peak usage times, scheduled events, regulatory implications
2. Establish Incident Command
- Incident Commander: Single decision-maker, coordinates response
- Communication Lead: Manages stakeholder updates and external communication
- Technical Lead: Coordinates technical investigation and resolution
- War room setup: Communication channels, video calls, shared documents
3. Immediate Stabilization
- Quick wins: Traffic throttling, feature flags, circuit breakers
- Rollback assessment: Recent deployments, configuration changes, infrastructure changes
- Resource scaling: Auto-scaling triggers, manual scaling, load redistribution
- Communication: Initial status page update, internal notifications
Modern Investigation Protocol
Observability-Driven Investigation
- Distributed tracing: OpenTelemetry, Jaeger, Zipkin for request flow analysis
- Metrics correlation: Prometheus, Grafana, DataDog for pattern identification
- Log aggregation: ELK, Splunk, Loki for error pattern analysis
- APM analysis: Application performance monitoring for bottleneck identification
- Real User Monitoring: User experience impact assessment
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.
- today First seen · 191 lines · 70 tokens per session scan A c330c05ec267
incident-responder is an agent published in the GitHub repository EngineerWithAI/engineerwith-agents (4 stars, last pushed 7mo ago), licensed MIT. It adds 70 tokens to every session and 1,980 once invoked, about $0.0003 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 2026-09-03.
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