Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add aizech/clinical-skills --skill model-validationgit clone --depth 1 https://github.com/aizech/clinical-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aizech/clinical-skills/model-validation)<a href="https://agentmods.dev/skills/aizech/clinical-skills/model-validation"><img src="https://agentmods.dev/badge/skills/aizech/clinical-skills/model-validation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aizech/clinical-skills/model-validation"><img src="https://agentmods.dev/badge/skills/aizech/clinical-skills/model-validation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00049 | $0.00569 |
| Opus 5.5 | $0.00020 | $0.00228 |
| Sonnet 5.5 | $0.00010 | $0.00114 |
| Haiku 4.5 | $0.00005 | $0.00057 |
Grade A, and why
model-validation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Model Validation Skill
Triggers
- "validate model performance"
- "external validation"
- "statistical analysis"
- "clinical validation"
- "model comparison"
- "regulatory submission"
- "performance benchmarking"
- "fairness audit"
Parameters
validation_type(required): Type of validation neededinternal- Retrospective internal datasetexternal- Prospective/out-of-distribution testingprospective- Clinical deployment studyregulatory- FDA/EMA submission prepfairness- Subgroup disparity analysiscomparison- Head-to-head model comparison
model_task(required): Model's intended usedetection- Sensitivity, specificity, PPV, NPVsegmentation- Dice, IoU, Hausdorff distanceclassification- Accuracy, AUC, F1 scoreregression- MAE, RMSE, correlation
modality(optional): Imaging modalityregulatory_path(optional): Target clearance pathway
Validation Framework
Performance Metrics
| Task | Primary Metrics | Secondary |
|---|---|---|
| Detection | Sensitivity, Specificity, AUC | PPV, NPV, FROC |
| Segmentation | Dice, IoU | Hausdorff, ASD |
| Classification | Accuracy, AUC, F1 | Sensitivity, Specificity |
| Regression | MAE, RMSE | Correlation, Bland-Altman |
Statistical Methods
- Confidence intervals (bootstrap, binominal)
- Significance testing (McNemar, DeLong for AUC)
- Power analysis for sample sizing
- Multiple comparison correction
- Subgroup interaction testing
Regulatory Standards
- FDA 510(k) predicate comparison
- FDA De Novo requirements
- EU MDR clinical evaluation
- IMDRF clinical evidence framework
- ACR-SIIM AI performance standards
Output Format
Returns structured JSON with:
- Validation protocol and methodology
- Required sample size with power analysis
- Statistical test selection and rationale
- Results template with standard metrics
- Interpretation guidelines
- Regulatory compliance checklist
Usage Examples
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 81 lines · 49 tokens per session scan A b644a4865482
model-validation is a skill published in the GitHub repository aizech/clinical-skills (6 stars, last pushed 4mo ago), licensed MIT. It adds 49 tokens to every session and 569 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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mfa-pipeline-orchestrator
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