Bio Instrument Data logo

Bio Instrument Data

Organization
frumu-ai
bio-instrument-data

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.

Overview

Publisherfrumu-ai
Repositorytandem
Skill namebio-instrument-data
Stars
121
Forks
13
Bundled files
Instructions only
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by frumu-ai on GitHub. Read the source before you install it.

Installation

Install the Bio Instrument Data AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/frumu-ai/tandem.git /tmp/tandem
mkdir -p .claude/skills
cp -r /tmp/tandem/apps/tandem-desktop/src-tauri/resources/skill-templates/bio-instrument-data .claude/skills/bio-instrument-data
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bio Instrument Data in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Bio Instrument Data on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Bio Instrument Data is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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 skill utilizes the Bio-Informatics Pack. Scripts and references are located in: src-tauri/resources/packs/bio-informatics-pack/allotrope-conversion/

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)
    • Python parser code (for data engineer handoff)
  4. Deliver files with summary and usage instructions

When Uncertain: If you're unsure how to map a field to ASM (e.g., is this raw data or calculated?), ask the user for clarification. Refer to the pack's references/field_classification_guide.md for guidance.

Quick Start

python
# Install requirements first
pip install allotropy pandas openpyxl pdfplumber --break-system-packages

# Core conversion
from allotropy.parser_factory import Vendor
from allotropy.to_allotrope import allotrope_from_file

# Convert with allotropy
asm = allotrope_from_file("instrument_data.csv", Vendor.BECKMAN_VI_CELL_BLU)

Output Format Selection

ASM JSON (default) - Full semantic structure with ontology URIs

  • Best for: LIMS systems expecting ASM, data lakes, long-term archival
  • Validates against Allotrope schemas

Flattened CSV - 2D tabular representation

  • Best for: Quick analysis, Excel users, systems without JSON support
  • Each measurement becomes one row with metadata repeated

Both - Generate both formats for maximum flexibility

Calculated Data Handling

IMPORTANT: Separate raw measurements from calculated/derived values.

  • Raw data → measurement-document (direct instrument readings)
  • Calculated data → calculated-data-aggregate-document (derived values)

Calculated values MUST include traceability via data-source-aggregate-document.

Validation

Always validate ASM output before delivering to the user:

bash
# Run validation script from the pack
python src-tauri/resources/packs/bio-informatics-pack/allotrope-conversion/scripts/validate_asm.py output.json

Frequently asked questions

What does the Bio Instrument Data AI 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.

Why use Bio Instrument Data on TypingMind?

Because you install it once and use it with any model. Bio Instrument Data is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Bio Instrument Data in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/frumu-ai/tandem/tree/main/apps/tandem-desktop/src-tauri/resources/skill-templates/bio-instrument-data. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Bio Instrument Data?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Bio Instrument Data?

As many as you like. As long as a model supports skills, you can use Bio Instrument Data with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Bio Instrument Data AI skill free?

It is published on GitHub by frumu-ai. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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