scientific-audit-report

Generate structured markdown audit reports for experimental data provenance.

3|1|Updated Feb 11, 2026

Search Tags:#logging #audit #compliance #provenance #reproducibility #data-lineage

Ready to run

npx skills add https://github.com/nahisaho/satori --skill scientific-audit-report

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: scientific-audit-report
Source: https://github.com/nahisaho/satori/tree/main/src/.github/skills/scientific-audit-report
Command: npx skills add https://github.com/nahisaho/satori --skill scientific-audit-report

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates audit trails and provenance reports for experimental data to support regulatory compliance and reproducibility.

Core Features & Use Cases

Audit trail generation: capture input data, transformations, outputs with timestamps and tool versions.
Provenance documentation: record environment, libraries, and configurations for reproducibility.
Compliance-ready outputs: produce structured audit reports suitable for GLP/GMP/GCP standards.

Quick Start

Scan experiment logs (messages.jsonl) and construct a provenance timeline from conversation.md and change histories.

Frequently Asked Questions about scientific-audit-report

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate an audit trail for experimental data to meet GLP compliance?▼

To generate an audit trail for experimental data, the tool scans experiment logs and conversation histories to capture inputs, transformations, and outputs. It produces a structured markdown provenance report suitable for GLP, GMP, and GCP compliant workflows.

What is data provenance and how does computational environment tracking support reproducibility?▼

Data provenance documents the lineage of experimental data by recording computational environments, library versions, and configurations. Tracking these computational environments supports reproducibility by ensuring transformations can be replicated accurately.

How to document data lineage and transformations from messages.jsonl logs?▼

Document data lineage by scanning messages.jsonl experiment logs alongside conversation histories to construct a provenance timeline. This process captures intermediate steps, tool versions, and timestamps to map data transformations.

Can I use automated provenance reports for GMP and GCP compliant workflows?▼

Yes, you can use automated provenance reports for GMP and GCP compliant workflows. The generated audit trails capture required data lineage, tool versions, and environment details in a structured markdown format to meet compliance standards.

What is the best way to capture tool versions and library configurations for reproducibility?▼

The best way to capture tool versions and library configurations is to automate provenance documentation during experimental data processing. This records environment details and transformation steps to generate a structured reproducibility report.

Does the generated audit report include timestamps for intermediate transformation steps?▼

Yes, the generated audit report includes timestamps for intermediate transformation steps. It captures inputs, outputs, and intermediate steps with precise timestamps to construct a comprehensive provenance timeline for experimental data.