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Skills ebm-calculator

Evidence-Based Medicine calculator for sensitivity, specificity, PPV,

install
source · Clone the upstream repo
git clone https://github.com/openclaw/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/aipoch-ai/ebm-calculator" ~/.claude/skills/openclaw-skills-ebm-calculator && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/aipoch-ai/ebm-calculator" ~/.openclaw/skills/openclaw-skills-ebm-calculator && rm -rf "$T"
manifest: skills/aipoch-ai/ebm-calculator/SKILL.md
tags
#ebm#biostatistics#calculator#clinical-reasoning#medical-statistics#diagnostic-testing
source content

EBM Calculator

Evidence-Based Medicine diagnostic test calculator.

Features

  • Sensitivity / Specificity calculation
  • PPV / NPV with prevalence adjustment
  • Likelihood ratios (LR+ / LR-)
  • Number Needed to Treat (NNT)
  • Pre/post-test probability conversion

Parameters

ParameterTypeDefaultRequiredDescription
--mode
, 
-m
stringdiagnosticNoCalculation mode (diagnostic, nnt, probability)
--tp
, 
--true-pos
int-*True positives (diagnostic mode)
--fn
, 
--false-neg
int-*False negatives (diagnostic mode)
--tn
, 
--true-neg
int-*True negatives (diagnostic mode)
--fp
, 
--false-pos
int-*False positives (diagnostic mode)
--prevalence
, 
-p
float-NoDisease prevalence 0-1 (diagnostic mode)
--control-rate
float-**Control event rate 0-1 (nnt mode)
--experimental-rate
float-**Experimental event rate 0-1 (nnt mode)
--pretest
float-***Pre-test probability 0-1 (probability mode)
--lr
float-***Likelihood ratio (probability mode)
--output
, 
-o
stringstdoutNoOutput file path

* Required for diagnostic mode
** Required for nnt mode
*** Required for probability mode

Output Format

{
  "sensitivity": "float",
  "specificity": "float",
  "ppv": "float",
  "npv": "float",
  "lr_positive": "float",
  "lr_negative": "float",
  "interpretation": "string"
}

Risk Assessment

Risk IndicatorAssessmentLevel
Code ExecutionPython/R scripts executed locallyMedium
Network AccessNo external API callsLow
File System AccessRead input files, write output filesMedium
Instruction TamperingStandard prompt guidelinesLow
Data ExposureOutput files saved to workspaceLow

Security Checklist

  • No hardcoded credentials or API keys
  • No unauthorized file system access (../)
  • Output does not expose sensitive information
  • Prompt injection protections in place
  • Input file paths validated (no ../ traversal)
  • Output directory restricted to workspace
  • Script execution in sandboxed environment
  • Error messages sanitized (no stack traces exposed)
  • Dependencies audited

Prerequisites

No additional Python packages required.

Evaluation Criteria

Success Metrics

  • Successfully executes main functionality
  • Output meets quality standards
  • Handles edge cases gracefully
  • Performance is acceptable

Test Cases

  1. Basic Functionality: Standard input → Expected output
  2. Edge Case: Invalid input → Graceful error handling
  3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

  • Current Stage: Draft
  • Next Review Date: 2026-03-06
  • Known Issues: None
  • Planned Improvements:
    • Performance optimization
    • Additional feature support