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Get Started Free →You are a monitoring and observability expert specializing in implementing comprehensive monitoring solutions. Set up metrics collection, distributed tracing, log aggregation, and create insightful da
.claude/skills/dokhacgiakhoa-observability-monitoring-monitor-setup/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-08 | ✗→✓ | ▲ Improved | 2% | 0% |
| case-12 | ✗→✓ | ▲ Improved | 8% | 0% |
| case-19 | ✗→✓ | ▲ Improved | 5% | 0% |
| case-21 | ✗→✓ | ▲ Improved | 44% | 0% |
| case-04 | ✓→✗ | ▼ Worse | 81% | 0% |
You are a monitoring and observability expert specializing in implementing comprehensive monitoring solutions. Set up metrics collection, distributed tracing, log aggregation, and create insightful dashboards that provide full visibility into system health and performance.
The user needs to implement or improve monitoring and observability. Focus on the three pillars of observability (metrics, logs, traces), setting up monitoring infrastructure, creating actionable dashboards, and establishing effective alerting strategies.
$ARGUMENTS
resources/implementation-playbook.md.Focus on creating a monitoring system that provides actionable insights, reduces MTTR, and enables proactive issue detection.
resources/implementation-playbook.md for detailed patterns and examples.| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 44,143 | 45,627 | +3% | 1 | 1 | 0% | 8,304 | 8,695 | +5% | 0 | 0 | — |
case-02 | fail→fail | 46,570 | 44,393 | -5% | 1 | 1 | 0% | 8,293 | 8,684 | +5% | 0 | 0 | — |
case-03 | fail→fail | 43,326 | 42,843 | -1% | 1 | 1 | 0% | 8,271 | 8,662 | +5% | 0 | 0 | — |
case-04 | pass→fail | 15,042 | 24,808 | +65% | 1 | 1 | 0% | 2,562 | 4,644 | +81% | 0 | 0 | — |
case-05 | pass→fail | 13,533 | 26,092 | +93% | 1 | 1 | 0% | 2,524 | 5,394 | +114% | 0 | 0 | — |
case-06 | pass→fail | 9,350 | 19,355 | +107% | 1 | 1 | 0% | 1,752 | 3,810 | +117% | 0 | 0 | — |
case-07 | pass→pass | 30,264 | 43,185 | +43% | 1 | 1 | 0% | 5,451 | 8,619 | +58% | 0 | 0 | — |
case-08 | fail→pass | 40,475 | 38,307 | -5% | 1 | 1 | 0% | 7,715 | 7,866 | +2% | 0 | 0 | — |
case-09 | fail→fail | 43,346 | 34,224 | -21% | 1 | 1 | 0% | 8,193 | 7,393 | -10% | 0 | 0 | — |
case-10 | pass→pass | 41,859 | 39,558 | -5% | 1 | 1 | 0% | 8,230 | 8,245 | +0% | 0 | 0 | — |
case-11 | fail→fail | 34,445 | 41,484 | +20% | 1 | 1 | 0% | 7,412 | 8,608 | +16% | 0 | 0 | — |
case-12 | fail→pass | 51,678 | 40,706 | -21% | 1 | 1 | 0% | 7,967 | 8,613 | +8% | 0 | 0 | — |
case-13 | pass→pass | 23,234 | 36,622 | +58% | 1 | 1 | 0% | 4,187 | 7,254 | +73% | 0 | 0 | — |
case-14 | fail→fail | 52,132 | 41,031 | -21% | 1 | 1 | 0% | 7,794 | 7,855 | +1% | 0 | 0 | — |
case-15 | fail→fail | 22,375 | 39,287 | +76% | 1 | 1 | 0% | 3,956 | 7,648 | +93% | 0 | 0 | — |
case-16 | fail→fail | 42,141 | 39,158 | -7% | 1 | 1 | 0% | 8,217 | 7,648 | -7% | 0 | 0 | — |
case-17 | pass→fail | 63,070 | 27,955 | -56% | 1 | 1 | 0% | 4,143 | 4,957 | +20% | 0 | 0 | — |
case-18 | pass→pass | 48,759 | 41,020 | -16% | 1 | 1 | 0% | 8,218 | 8,609 | +5% | 0 | 0 | — |
case-19 | fail→pass | 41,109 | 44,192 | +7% | 1 | 1 | 0% | 8,214 | 8,605 | +5% | 0 | 0 | — |
case-20 | fail→fail | 41,873 | 36,484 | -13% | 1 | 1 | 0% | 7,199 | 7,206 | +0% | 0 | 0 | — |
case-21 | fail→pass | 28,204 | 35,855 | +27% | 1 | 1 | 0% | 4,934 | 7,085 | +44% | 0 | 0 | — |
case-22 | fail→fail | 24,726 | 35,459 | +43% | 1 | 1 | 0% | 3,780 | 6,834 | +81% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of 0 percentage points is the difference between those two pass rates over the 22 comparable cases. 5 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.