Clinical Trial Schema Designer
- 163 installs
- 2 repo stars
- Updated January 25, 2026
- jorgealves/agent_skills
Design normalized clinical-trial data models with visit schedules, arms, endpoints, and regulatory traceability before EDC or warehouse implementation.
About
clinical-trial-schema-designer guides agents to produce rigorous database schemas for regulated clinical studies, covering subjects, sites, arms, visits, forms, and endpoints. It emphasizes auditability, referential integrity, and standards-aware naming so trial data can feed EDC, analytics, and compliance reporting.
- Models visits, cohorts, randomization, and adverse events
- Encodes regulatory audit fields and versioning patterns
- Balances FHIR/CDISC alignment with pragmatic SQL shapes
- Flags cardinality traps in longitudinal trial data
- Produces reviewable DDL-ready table definitions
Clinical Trial Schema Designer by the numbers
- 163 all-time installs (skills.sh)
- +10 installs in the week ending Aug 2, 2026 (Skillselion tracking)
- Ranked #254 of 911 Databases skills by installs in the Skillselion catalog
- Data as of Aug 2, 2026 (Skillselion catalog sync)
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| Installs | 163 |
|---|---|
| repo stars | ★ 2 |
| Last updated | January 25, 2026 |
| Repository | jorgealves/agent_skills ↗ |
What it does
Design normalized clinical-trial data models with visit schedules, arms, endpoints, and regulatory traceability before EDC or warehouse implementation.
Files
Clinical Trial Schema Designer
Purpose and Intent
The clinical-trial-schema-designer bridges the gap between clinical research and data engineering. It helps automate the creation of standardized data structures (CDISC) based on clinical protocols, reducing the manual effort required for data ingestion and submission preparation.
When to Use
- Study Setup: Use during the "Start-up" phase of a clinical trial to design the Electronic Data Capture (EDC) schemas.
- Data Integration: When merging data from multiple sources into a single study standard.
- Submission Prep: To ensure the data structure matches FDA/PMDA requirements for SDTM/ADaM.
When NOT to Use
- Unvalidated Systems: Clinical data must be handled in GxP-validated environments. This tool generates the design, but the implementation must follow strict validation protocols.
- Medical Decision Making: This is a data structuring tool, not a clinical diagnostic or treatment tool.
Error Conditions and Edge Cases
- Ambiguous Protocols: If the input text is vague about how a variable is measured, the generated schema may be incomplete.
- Non-Standard Studies: Phase 1 or highly experimental studies may use variables that don't fit existing CDISC domains perfectly.
Security and Data-Handling Considerations
- IP Protection: Clinical protocols are intellectual property. Ensure the environment running this skill is secure.
- No Patient Data: This tool works on protocols (the plan), not the actual results (the data).
name: clinical-trial-schema-designer
version: 1.0.0
description: Analyzes clinical trial protocols and generates CDISC-compliant (SDTM/ADaM) data schemas. Use when designing data ingestion pipelines for clinical research or preparing regulatory submissions.
inputs:
protocol_text:
type: string
description: The raw text of the clinical trial protocol.
required: true
target_standard:
type: string
enum: [SDTM, ADaM, CDASH]
default: SDTM
outputs:
schema_definition:
type: object
description: The generated data schema in JSON format.
mapping_logic:
type: array
items:
type: string
capabilities:
- Study variable extraction (Demographics, Adverse Events).
- Automated CDISC domain mapping.
- Pydantic/SQL schema generation.
constraints:
- Accuracy depends on protocol text quality.
- Custom designs may require manual refinement.
security:
- Protocols are intellectual property; process securely.
- Does not handle actual patient results.
examples:
- input:
protocol_text: "Study will track heart rate daily..."
output:
schema_definition:
domain: "VS"
variables: ["VSTESTCD", "VSORRES"]
mapping_logic: ["Map 'heart rate' to VSTESTCD='HR'"]Related skills
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