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 skills add ancoleman/ai-design-components --skill managing-incidentsgit clone --depth 1 https://github.com/ancoleman/ai-design-componentsWrote 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/ancoleman/ai-design-components/managing-incidents)<a href="https://agentmods.dev/skills/ancoleman/ai-design-components/managing-incidents"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/managing-incidents/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/ancoleman/ai-design-components/managing-incidents"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/managing-incidents.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 | $0.00054 | $0.03256 |
| Opus 5 | $0.00027 | $0.01628 |
| Sonnet 5 | $0.00011 | $0.00651 |
| Haiku 4.5 | $0.00005 | $0.00326 |
Grade A, and why
managing-incidents 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 11d 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 — 434 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Incident Management
Provide end-to-end incident management guidance covering detection, response, communication, and learning. Emphasizes SRE culture, blameless post-mortems, and structured processes for high-reliability operations.
When to Use This Skill
Apply this skill when:
- Setting up incident response processes for a team
- Designing on-call rotations and escalation policies
- Creating runbooks for common failure scenarios
- Conducting blameless post-mortems after incidents
- Implementing incident communication protocols (internal and external)
- Choosing incident management tooling and platforms
- Improving MTTR and incident frequency metrics
Core Principles
Incident Management Philosophy
Declare Early and Often: Do not wait for certainty. Declaring an incident enables coordination, can be downgraded if needed, and prevents delayed response.
Mitigation First, Root Cause Later: Stop customer impact immediately (rollback, disable feature, failover). Debug and fix root cause after stability restored.
Blameless Culture: Assume good intentions. Focus on how systems failed, not who failed. Create psychological safety for honest learning.
Clear Command Structure: Assign Incident Commander (IC) to own coordination. IC delegates tasks but does not do hands-on debugging.
Communication is Critical: Internal coordination via dedicated channels, external transparency via status pages. Update stakeholders every 15-30 minutes during critical incidents.
Severity Classification
Standard severity levels with response times:
SEV0 (P0) - Critical Outage:
- Impact: Complete service outage, critical data loss, payment processing down
- Response: Page immediately 24/7, all hands on deck, executive notification
- Example: API completely down, entire customer base affected
SEV1 (P1) - Major Degradation:
- Impact: Major functionality degraded, significant customer subset affected
- Response: Page during business hours, escalate off-hours, IC assigned
- Example: 15% error rate, critical feature unavailable
What ships with it
17 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- examples/communication-templates.md 16 KB
- examples/integrations/pagerduty-slack.py 8.5 KB runs code
- examples/integrations/postmortem-generator.py 7.6 KB runs code
- examples/integrations/statuspage-auto-update.py 7.2 KB runs code
- examples/oncall-handoff-template.md 12 KB
- examples/postmortem-template.md 13 KB
- examples/runbooks/cache-invalidation.md 19 KB
- examples/runbooks/database-failover.md 12 KB
- examples/runbooks/ddos-mitigation.md 29 KB
- outputs.yaml 7.5 KB
- references/blameless-postmortems.md 22 KB
- references/escalation-matrix.md 4.3 KB
- references/incident-roles.md 17 KB
- references/incident-workflow.md 7.4 KB
- references/severity-classification.md 14 KB
- references/tool-comparison.md 17 KB
- scripts/classify-severity.py 14 KB runs code
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.
- 11d ago First seen · 434 lines · 54 tokens per session scan A 67ca93bc92c0
managing-incidents is a skill published in the GitHub repository ancoleman/ai-design-components (517 stars, last pushed 9mo ago), licensed MIT. It adds 54 tokens to every session and 3,256 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 2026-08-30.
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