Does it separate raw data from calculated results?

Yes, the skill follows strict ASM standards by separating 'measurement-documents' from 'calculated-data-aggregate-documents' to maintain full data traceability.

Which instrument vendors are supported?

The skill supports a wide range of major vendors including Agilent, Beckman Coulter, Thermo Fisher, Molecular Devices, Bio-Rad, and many others via the allotropy library.

Is the generated Python code usable in production environments?

Absolutely. The skill can export standalone Python scripts that are self-contained and production-ready, making them ideal for integration into automated data pipelines.

Can it handle PDF reports from instruments?

Yes, it utilizes PDF extraction strategies to pull tabular data and metadata from instrument reports, then maps them to the appropriate ASM schema.

Why use the Allotrope Simple Model (ASM)?

ASM provides a standardized, vendor-neutral format for lab data using semantic web technologies, ensuring your scientific data remains interoperable and accessible over the long term.

Lab Instrument Data Converter

Name: Lab Instrument Data Converter
Author: anthropics

byanthropics

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8,000

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Data Science & ML

Standardizes laboratory instrument data by converting various file formats into the Allotrope Simple Model (ASM) for LIMS and downstream analysis.

This skill streamlines bio-research workflows by automating the transformation of heterogeneous laboratory data—from spectrophotometers and cell counters to plate readers and qPCR machines—into the industry-standard Allotrope Simple Model (ASM). It simplifies complex data engineering tasks by auto-detecting instrument types, distinguishing between raw and calculated data with full traceability, and providing multiple output formats. Whether you need semantic JSON for a data lake, a flattened CSV for a LIMS upload, or production-ready Python code for a data pipeline, this skill ensures your lab data is FAIR (Findable, Accessible, Interoperable, and Reusable).

Key Features

01Generates flattened 2D CSV files for easy analysis in Excel or integration with legacy LIMS.

02Auto-detects instrument types and vendors from file contents (e.g., Agilent, Beckman, Thermo Fisher).

03Validates data against Allotrope semantic schemas to ensure ontology and unit compliance.

048,000 GitHub stars

05Exports standalone, production-ready Python parser code for data engineering handoffs.

06Parses PDF, CSV, Excel, and TXT outputs into structured Allotrope Simple Model (ASM) JSON.

Use Cases

01Standardizing heterogeneous lab results for seamless upload to a LIMS or Electronic Lab Notebook (ELN).

02Preparing large-scale instrument datasets for long-term archival and queryability in a cloud data lake.

03Automating the generation of custom data parsing scripts for bioinformatics and data engineering pipelines.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add anthropics/knowledge-work-plugins instrument-data-to-allotrope

For use in Claude.ai and ChatGPT

Download Skill