Borrowing it
Nothing to install: this file belongs to irahardianto/awesome-agv. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/irahardianto/awesome-agv/main/.agents/skills/incident-response/SKILL.mdgit clone --depth 1 https://github.com/irahardianto/awesome-agvWrote 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/irahardianto/awesome-agv/incident-response)<a href="https://agentmods.dev/skills/irahardianto/awesome-agv/incident-response"><img src="https://agentmods.dev/badge/skills/irahardianto/awesome-agv/incident-response/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/irahardianto/awesome-agv/incident-response"><img src="https://agentmods.dev/badge/skills/irahardianto/awesome-agv/incident-response.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 171 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 172 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00032 | $0.01358 |
| Opus 5 | $0.00016 | $0.00679 |
| Sonnet 5 | $0.00006 | $0.00272 |
| Haiku 4.5 | $0.00003 | $0.00136 |
Grade A, and why
incident-response 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- incident-response — 88% identical, 6 lines differ
How it starts
The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Incident Response
Structured framework for handling production incidents with blameless postmortems.
When to Invoke
- Production incidents (P0-P3)
- Service degradation or outages
- Post-incident analysis and learning
- Improving incident response processes
Severity Classification
| Severity | Impact | Response Time | Examples |
|---|---|---|---|
| P0 | Complete outage, data loss risk | Immediate (< 15 min) | Service down, data corruption |
| P1 | Major degradation, many users affected | < 30 min | Core feature broken, severe performance |
| P2 | Partial degradation, some users | < 2 hours | Non-critical feature broken, slow queries |
| P3 | Minor issue, workaround available | < 1 business day | UI glitch, minor performance |
Incident Workflow
1. Detect & Alert
- Automated monitoring triggers alert
- User reports issue
- On-call engineer acknowledges
2. Triage
- Classify severity (P0-P3)
- Assess blast radius (users, services, data)
- Identify incident commander
- Open communication channel
3. Diagnose
- Form hypotheses (use
debugging-protocolskill) - Collect evidence (logs, traces, metrics)
- Identify root cause
- Document timeline
4. Mitigate
- Implement immediate fix (rollback, feature flag, hotfix)
- Verify mitigation effectiveness
- Communicate status to stakeholders
- Continue monitoring
5. Resolve
- Confirm service fully recovered
- Close incident
- Schedule postmortem (within 48 hours for P0-P2)
Postmortem Template
# Incident Postmortem: {title}
Date: {date}
Severity: P{0-3}
Duration: {start} → {resolved}
Author: {name}
## Summary
{1-2 sentence impact summary}
## Timeline
| Time | Event |
|---|---|
| HH:MM | {event description} |
## Root Cause
{description with evidence}
## Contributing Factors
- {factor with context}
## What Went Well
- {positive observation}
## What Could Be Improved
- {improvement area}
## Action Items
| Action | Owner | Due Date | Status |
|---|---|---|---|
| {specific action} | @{person} | YYYY-MM-DD | Open |
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 · 174 lines · 32 tokens per session scan A 83895fe4f60e
incident-response is a skill published in the GitHub repository irahardianto/awesome-agv (156 stars, last pushed 21d ago), licensed MIT. It adds 32 tokens to every session and 1,358 once invoked, about $0.0002 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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