Radiology metrics

Skill aizech/clinical-skills/.cortex/skills/radiology-metrics

Retrieves and analyzes operational metrics from radiology information systems. Use when user mentions "radiology KPIs", "productivity metrics", "turnaround time analysis", "workload distribution", or needs operational analytics.From its SKILL.md

Install

npx -y skills add aizech/clinical-skills --skill radiology-metrics

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One thing to look at

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SKILL.md

1.9 KB, 379 tokens by cl100k_base, as published. Nobody here has run it

Radiology Metrics Skill

Triggers

"radiology KPIs"
"productivity metrics"
"turnaround time analysis"
"workload distribution"
"RVU tracking"
"department dashboard"
"volume forecasting"

Parameters

metric_type (required): Type of metrics to retrieve
- turnaround_time - Report TAT analysis
- productivity - Studies per radiologist, modality counts
- utilization - Equipment and room utilization rates
- quality - Accuracy, discrepancy, critical result rates
- financial - RVUs, revenue, cost per study
- volume - Historical and forecasted volumes
time_range (optional): Analysis period - defaults to last 30 days
group_by (optional): Segmentation - radiologist, modality, location, urgency
compare_previous (optional): Include period-over-period comparison

Data Sources

RIS (Radiology Information System) for report data
PACS for study volumes and workflow timestamps
Scheduler for utilization and capacity data
Historical databases for trend analysis

Output Format

Returns structured JSON with:

Primary metrics (requested type)
Trend indicators (vs. previous period)
Benchmark comparisons where available
Anomaly alerts for statistical outliers
Recommended actions for improvement areas

Usage Examples

metric_type: turnaround_time
time_range: last_month
group_by: [modality, urgency]

metric_type: productivity
time_range: last_quarter
compare_previous: true

Error Handling

Missing RIS data: Report partial results with data gap indicators
Insufficient history: Expand time range suggestion
Permission denied: Request escalated access with justification

What ships with it: 1 file

3.3 KB alongside SKILL.md

evals/

evals.json3.3 KB

Gives 0 of the 12 instructions most healthcare skills give in 379 tokens

Counted across 147 of the 152 authors here whose files we hold, read 2026-08-07

Export trial data to CSV formatin 11 of 147, across 2 files
Retrieve trial details using an NCT IDin 11 of 147, across 2 files
Split clinical datasets strictly by patientin 11 of 147, across 3 files
Use the ClinicalTrials.gov API v2in 10 of 147, across 1 file
Search trials by condition, drug, location, status or phasein 10 of 147, across 1 file
Use maximum page size for bulk data retrievalin 10 of 147, across 1 file
Extract and summarize key study informationin 10 of 147, across 1 file
Combine multiple filters for targeted searchesin 10 of 147, across 1 file
Print and review dataset statistics before modelingin 8 of 147, across 1 file
Start model development with simple baselinesin 8 of 147, across 1 file
Match preprocessing processors directly to data typesin 8 of 147, across 1 file
Monitor validation metrics for task type and class imbalancein 8 of 147, across 1 file

Said here and by no other author read

retrieve requested operational metrics
segment data by the requested group
include previous period comparisons
report trend indicators versus previous period
include benchmark comparisons when available
flag statistical outliers as anomaly alerts

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.