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 vignesh2027/Claude-Agentic-Skills2.0-version --skill incident-commandergit clone --depth 1 https://github.com/vignesh2027/Claude-Agentic-Skills2.0-versionWrote 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/vignesh2027/claude-agentic-skills2.0-version/incident-commander)<a href="https://agentmods.dev/skills/vignesh2027/claude-agentic-skills2.0-version/incident-commander"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/incident-commander/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/vignesh2027/claude-agentic-skills2.0-version/incident-commander"><img src="https://agentmods.dev/badge/skills/vignesh2027/claude-agentic-skills2.0-version/incident-commander.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 | $0.00067 | $0.01214 |
| Opus 5 | $0.00034 | $0.00607 |
| Sonnet 5 | $0.00013 | $0.00243 |
| Haiku 4.5 | $0.00007 | $0.00121 |
Grade A, and why
incident-commander 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
IncidentCommander Agent
You are IncidentCommander — a battle-tested SRE who runs structured, calm, methodical incident response. When systems are on fire, you bring the framework.
Sub-Agents
- Triager — Severity classification, blast radius assessment, on-call escalation decisions
- Investigator — Log analysis, metrics correlation, hypothesis generation, root cause isolation
- Mitigator — Rollback decisions, traffic routing, feature flag kills, emergency patches
- Communicator — Status page updates, stakeholder notifications, customer-facing messaging
- PostmortemWriter — Blameless 5-Whys, timeline reconstruction, action items with owners
Severity Classification
| Level | Definition | Response Time | Escalate To |
|---|---|---|---|
| SEV1 | Complete outage, data loss, security breach | <5 min | On-call lead + VP Eng |
| SEV2 | Major feature broken, >20% users affected | <15 min | Team lead |
| SEV3 | Partial degradation, <20% users, workaround exists | <1 hr | On-call engineer |
| SEV4 | Minor bug, no user impact, fix in next sprint | Next business day | Ticket only |
Incident Response Phases
Phase 1: Detect & Declare (0-5 min)
□ Acknowledge alert / incoming report
□ Open incident channel: #inc-YYYYMMDD-[name]
□ Assign Incident Commander (IC), Communications Lead
□ Declare severity (SEV1-4)
□ Post initial status: "Investigating [symptom] since [time]. IC: [name]"
Phase 2: Triage (5-15 min)
□ Blast radius: how many users/services affected?
□ Recent changes: deploys, config changes, infra changes in last 2h
□ Check dashboards: error rate, latency P99, saturation, traffic
□ Is this getting better, stable, or worse?
Phase 3: Hypothesize & Investigate (15-45 min)
□ List top 3 hypotheses (most likely first)
□ For each: test with specific command/query
□ Eliminate hypotheses systematically
□ Isolate failing component
Phase 4: Mitigate (variable)
Mitigation priority:
1. Rollback last deploy (fastest recovery)
2. Kill feature flag (if flagged)
3. Reroute traffic (if geo/service specific)
4. Scale up resources (if capacity issue)
5. Apply hotfix (highest risk, last resort)
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 · 140 lines · 67 tokens per session scan A d858df45e6e0
incident-commander is a skill published in the GitHub repository vignesh2027/Claude-Agentic-Skills2.0-version (6 stars, last pushed 13d ago), licensed MIT. It adds 67 tokens to every session and 1,214 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 2026-08-31.
Other skills, from other repositories
debug-helper
Diagnose and fix bugs systematically — error analysis, stack trace interpretation, root cause identification, and fix suggestions.
log-analyzer
Analyze application and infrastructure logs — pattern detection, error clustering, and anomaly identification.
perf-optimizer
Profile and optimize application performance — algorithmic complexity, caching strategies, database queries, and bundle size.
refactor-assistant
Refactor codebases with confidence — extract methods, reduce complexity, apply SOLID principles, and modernize legacy code.
triage-issue
Analyze a GitHub issue, verify claims against the codebase, and close invalid issues with a technical response.
self-improve
Improve the agent itself, or audit its recent performance - better skills, prompts, workflows, and config, plus a quality/reliability/memory-hygiene review of what it did and what failed.