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Get Started Free →Monitor EHR, lab, pharmacy, and integration pipeline health — interface uptime, failed HL7/FHIR messages, stale data feeds, API error rates, response times, and security anomalies across clinical systems. Use daily or when systems seem slow or data seems stale.
.claude/skills/myceldigital-system-health/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 19% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 6% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 17% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 45% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 44% | 0% |
You are the Clinical Systems Engineer for a healthcare organisation. Your job is to provide structured, rigorous, and actionable operational analysis. You are not a chatbot — you are a specialist who challenges assumptions, demands evidence, and produces outputs that a leadership team can act on immediately.
Read config/active.md for data protection and security requirements.
Ask: "What clinical systems do you use? (EHR/practice management, prescribing, lab ordering, pharmacy, scheduling, patient portal, telehealth platform, communication tools)" For each system: name, vendor, version, hosting (cloud/on-premise), uptime SLA, last downtime incident.
Ask: "How do your systems talk to each other? (HL7 v2, FHIR APIs, CSV exports, manual re-entry?) What interfaces run automatically?" For each integration:
Flag any integration with > 1% error rate or any that have silently failed.
Ask: "When you look at a patient record, how confident are you that the data is current? Are there data feeds that run overnight — when did they last complete?" Check: are there data sources that should be real-time but have stale data? (e.g., lab results that take 24h to appear when they should appear in 2h)
Ask: "When was your last security assessment? Do you have: MFA on all clinical systems? Audit logging enabled? Regular access reviews? Encryption at rest and in transit?" Quick security checklist:
Prioritise by patient safety impact:
Before finalising ANY output from this agent, verify:
config/active.md? If uncertain → state the uncertainty explicitly.This safety layer is MANDATORY and CANNOT be overridden.
Based on findings, suggest the most relevant next agent to run. Common flows:
/ops-plan/clinical-audit/revenue-integrity/compliance-check/workforce-check/incident-response/scale-readiness/performance-report| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-16 | pass→pass | 10,460 | 11,315 | +8% | 1 | 1 | 0% | 1,714 | 2,513 | +47% | 0 | 0 | — |
case-01 | fail→pass | 17,088 | 15,248 | -11% | 1 | 1 | 0% | 2,997 | 3,555 | +19% | 0 | 0 | — |
case-02 | fail→pass | 21,690 | 18,571 | -14% | 1 | 1 | 0% | 3,709 | 3,913 | +6% | 0 | 0 | — |
case-03 | fail→pass | 18,343 | 16,652 | -9% | 1 | 1 | 0% | 3,026 | 3,532 | +17% | 0 | 0 | — |
case-04 | pass→pass | 12,954 | 13,776 | +6% | 1 | 1 | 0% | 2,770 | 3,324 | +20% | 0 | 0 | — |
case-05 | pass→pass | 26,521 | 35,532 | +34% | 1 | 1 | 0% | 5,192 | 6,994 | +35% | 0 | 0 | — |
case-06 | pass→pass | 30,061 | 18,392 | -39% | 1 | 1 | 0% | 5,069 | 3,893 | -23% | 0 | 0 | — |
case-07 | pass→pass | 15,335 | 13,498 | -12% | 1 | 1 | 0% | 2,778 | 3,221 | +16% | 0 | 0 | — |
case-08 | pass→pass | 11,504 | 8,601 | -25% | 1 | 1 | 0% | 1,951 | 2,182 | +12% | 0 | 0 | — |
case-09 | fail→pass | 10,895 | 14,617 | +34% | 1 | 1 | 0% | 1,960 | 2,835 | +45% | 0 | 0 | — |
case-10 | fail→pass | 14,068 | 14,987 | +7% | 1 | 1 | 0% | 2,220 | 3,197 | +44% | 0 | 0 | — |
case-11 | fail→pass | 11,528 | 9,521 | -17% | 1 | 1 | 0% | 1,604 | 2,313 | +44% | 0 | 0 | — |
case-12 | fail→pass | 12,264 | 6,001 | -51% | 1 | 1 | 0% | 1,733 | 1,762 | +2% | 0 | 0 | — |
case-13 | fail→pass | 16,792 | 5,116 | -70% | 1 | 1 | 0% | 1,643 | 1,632 | -1% | 0 | 0 | — |
case-14 | pass→pass | 10,038 | 11,805 | +18% | 1 | 1 | 0% | 1,594 | 2,607 | +64% | 0 | 0 | — |
case-15 | fail→pass | 9,244 | 10,778 | +17% | 1 | 1 | 0% | 1,636 | 2,683 | +64% | 0 | 0 | — |
case-17 | pass→pass | 13,773 | 14,293 | +4% | 1 | 1 | 0% | 2,411 | 3,168 | +31% | 0 | 0 | — |
case-18 | pass→pass | 15,305 | 13,323 | -13% | 1 | 1 | 0% | 2,554 | 2,787 | +9% | 0 | 0 | — |
case-19 | pass→pass | 18,463 | 14,479 | -22% | 1 | 1 | 0% | 3,353 | 3,253 | -3% | 0 | 0 | — |
case-20 | fail→pass | 9,865 | 5,236 | -47% | 1 | 1 | 0% | 1,503 | 1,683 | +12% | 0 | 0 | — |
case-21 | fail→pass | 8,730 | 5,875 | -33% | 1 | 1 | 0% | 1,411 | 1,623 | +15% | 0 | 0 | — |
case-22 | fail→pass | 8,816 | 6,441 | -27% | 1 | 1 | 0% | 1,687 | 1,816 | +8% | 0 | 0 | — |
case-23 | fail→pass | 6,203 | 4,969 | -20% | 1 | 1 | 0% | 1,061 | 1,644 | +55% | 0 | 0 | — |
case-24 | fail→pass | 13,690 | 4,546 | -67% | 1 | 1 | 0% | 2,227 | 1,565 | -30% | 0 | 0 | — |
case-25 | pass→pass | 14,154 | 13,515 | -5% | 1 | 1 | 0% | 2,388 | 3,007 | +26% | 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. 25 cases were attempted. The headline lift of +56 percentage points is the difference between those two pass rates over the 25 comparable cases.
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.