compute_sps
Evaluate clinical AI models by computing a Security Posture Score from adversarial robustness, threat mitigation, audit completeness, and compliance inputs.
Instructions
Compose the Security Posture Score from four dimension inputs.
`auroc_drop` should be the WORST-CASE drop across all adversarial
attack runs performed (max, not mean, across FGSM/boundary and
any datasets evaluated) -- that's what the validated weighting
was calibrated against. `compliance_score` is a fraction (0-1),
e.g. `score_compliance`'s `overall_pct` divided by 100.
Returns the composite SPS (0-100), a deployment recommendation
tier, and each dimension's subscore/weight/contribution for a
transparent breakdown.
Tool call template
Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {
"auroc_drop": "<auroc_drop>",
"threat_mitigated": "<threat_mitigated>",
"threat_tested": "<threat_tested>",
"threat_total": "<threat_total>",
"threat_passed": "<threat_passed>",
"threat_partial": "<threat_partial>",
"audit_completeness_rate": "<audit_completeness_rate>",
"rbac_enforcement_rate": "<rbac_enforcement_rate>",
"compliance_score": "<compliance_score>"
},
"name": "compute_sps"
}
}Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| auroc_drop | Yes | ||
| threat_total | Yes | ||
| threat_passed | Yes | ||
| threat_tested | Yes | ||
| threat_partial | Yes | ||
| compliance_score | Yes | ||
| threat_mitigated | Yes | ||
| rbac_enforcement_rate | Yes | ||
| audit_completeness_rate | Yes |