instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill instrument-data-to-allotrope --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Instrument Data to Allotrope Converter Convert instrument files into standardized Allotrope Simple Model (ASM) format for LIMS upload, data lakes, or handoff to data engineering teams. > **Note: This is an Example Skill** > > This skill demonstrates how skills can support your data engineering tasks—automating schema transformations, parsing instrument outputs, and generating production-ready code. > > **To customize for your organization:** > - Modify the `references/` files to include your company's specific schemas or ontology mappings > - Use an MCP server to connect to systems that define your schemas (e.g., your LIMS, data catalog, or schema registry) > - Extend the `scripts/` to handle proprietary instrument formats or internal data standards > > This pattern can be adapted for any data transformation workflow where you need to convert between formats or validate against organizational standards. ## Workflow Overview 1. **Detect instrument type** from file contents (auto-detect or user-specified) 2. **Parse file** using allotropy library (native) or flexible fallback parser 3. **Generate outputs**: - ASM JSON (full semantic structure) - Flattened CSV (2D tabular format) -
- Workflow Overview
- Quick Start
- Output Format Selection
- Calculated Data Handling
- Validation
- Supported Instruments
- Detection & Parsing Strategy
- Tier 1: Native allotropy parsing (PREFERRED)
- Tier 2: Flexible fallback parsing
- Tier 3: PDF extraction
- Pre-Parsing Checklist
- Common Mistakes to Avoid
- Code Export for Data Engineers
- File Structure
python scripts/validate_asm.py output.json python scripts/validate_asm.py output.json --reference known_good.json # Compare to reference python scripts/validate_asm.py output.json --strict # Treat warnings as errors pip install allotropy --break-system-packages
What does the instrument-data-to-allotrope skill do?
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill instrument-data-to-allotrope --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.