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Get Started Free →Reviews healthcare application code for clinical safety, CDSS accuracy, PHI compliance, and medical data integrity. Specialized for EMR/EHR, clinical decision support, and health information systems.
.claude/skills/kunanonj-agent-healthcare-reviewer/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | -34% | 0% |
| case-02 | ✗→✓ | ▲ Improved | -54% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 17% | 0% |
| case-21 | ✓→✗ | ▼ Worse | 25% | 0% |
| case-23 | ✓→✗ | ▼ Worse | -6% | 0% |
You are a clinical informatics reviewer for healthcare software. Patient safety is your top priority. You review code for clinical accuracy, data protection, and regulatory compliance.
console.log, console.error, or error messagesservice_role key in client-side code## Healthcare Review: [module/feature]
### Patient Safety Impact: [CRITICAL / HIGH / MEDIUM / LOW / NONE]
### Clinical Accuracy
- CDSS: [checks passed/failed]
- Drug DB: [verified/issues]
- Scoring: [matches spec/deviates]
### PHI Compliance
- Exposure vectors checked: [list]
- Issues found: [list or none]
### Issues
1. [PATIENT SAFETY / CLINICAL / PHI / TECHNICAL] Description
- Impact: [potential harm or exposure]
- Fix: [required change]
### Verdict: [SAFE TO DEPLOY / NEEDS FIXES / BLOCK — PATIENT SAFETY RISK]| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 22,902 | 8,856 | -61% | 1 | 1 | 0% | 3,893 | 2,552 | -34% | 0 | 0 | — |
case-02 | fail→pass | 31,294 | 11,327 | -64% | 1 | 1 | 0% | 6,209 | 2,870 | -54% | 0 | 0 | — |
case-03 | fail→fail | 3,034 | 5,733 | +89% | 1 | 1 | 0% | 484 | 1,857 | +284% | 0 | 0 | — |
case-04 | pass→pass | 13,408 | 6,057 | -55% | 1 | 1 | 0% | 2,150 | 1,975 | -8% | 0 | 0 | — |
case-05 | pass→pass | 12,590 | 8,036 | -36% | 1 | 1 | 0% | 2,089 | 2,364 | +13% | 0 | 0 | — |
case-06 | fail→pass | 11,934 | 6,775 | -43% | 1 | 1 | 0% | 1,881 | 2,200 | +17% | 0 | 0 | — |
case-07 | pass→pass | 10,084 | 6,525 | -35% | 1 | 1 | 0% | 1,817 | 2,059 | +13% | 0 | 0 | — |
case-08 | pass→pass | 13,241 | 5,663 | -57% | 1 | 1 | 0% | 2,397 | 1,995 | -17% | 0 | 0 | — |
case-09 | pass→pass | 13,017 | 8,274 | -36% | 1 | 1 | 0% | 2,247 | 2,281 | +2% | 0 | 0 | — |
case-10 | pass→pass | 10,521 | 7,150 | -32% | 1 | 1 | 0% | 1,916 | 2,300 | +20% | 0 | 0 | — |
case-11 | pass→pass | 10,988 | 7,163 | -35% | 1 | 1 | 0% | 1,697 | 2,026 | +19% | 0 | 0 | — |
case-12 | pass→pass | 14,280 | 4,983 | -65% | 1 | 1 | 0% | 2,187 | 1,890 | -14% | 0 | 0 | — |
case-13 | pass→pass | 13,187 | 6,898 | -48% | 1 | 1 | 0% | 2,028 | 1,975 | -3% | 0 | 0 | — |
case-14 | pass→pass | 13,021 | 9,466 | -27% | 1 | 1 | 0% | 1,934 | 2,318 | +20% | 0 | 0 | — |
case-15 | pass→pass | 12,942 | 7,191 | -44% | 1 | 1 | 0% | 1,964 | 2,021 | +3% | 0 | 0 | — |
case-16 | pass→pass | 14,110 | 5,459 | -61% | 1 | 1 | 0% | 2,075 | 1,816 | -12% | 0 | 0 | — |
case-17 | pass→pass | 17,702 | 8,597 | -51% | 1 | 1 | 0% | 2,548 | 2,136 | -16% | 0 | 0 | — |
case-18 | pass→pass | 9,090 | 6,175 | -32% | 1 | 1 | 0% | 1,625 | 2,127 | +31% | 0 | 0 | — |
case-19 | pass→pass | 10,851 | 4,789 | -56% | 1 | 1 | 0% | 1,851 | 1,842 | -0% | 0 | 0 | — |
case-20 | pass→pass | 12,646 | 8,197 | -35% | 1 | 1 | 0% | 1,885 | 2,234 | +19% | 0 | 0 | — |
case-21 | pass→fail | 11,347 | 9,290 | -18% | 1 | 1 | 0% | 1,999 | 2,501 | +25% | 0 | 0 | — |
case-22 | pass→pass | 16,221 | 10,731 | -34% | 1 | 1 | 0% | 2,720 | 2,686 | -1% | 0 | 0 | — |
case-23 | pass→fail | 19,215 | 13,717 | -29% | 1 | 1 | 0% | 3,275 | 3,065 | -6% | 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. 23 cases were attempted. The headline lift of 0 percentage points is the difference between those two pass rates over the 23 comparable cases. 2 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.