instrument-data-allotrope-example-1-vi-cell-blu-file
Sub-skill of instrument-data-allotrope: Example 1: Vi-CELL BLU file (+2).
Best use case
instrument-data-allotrope-example-1-vi-cell-blu-file is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of instrument-data-allotrope: Example 1: Vi-CELL BLU file (+2).
Teams using instrument-data-allotrope-example-1-vi-cell-blu-file should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/example-1-vi-cell-blu-file/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How instrument-data-allotrope-example-1-vi-cell-blu-file Compares
| Feature / Agent | instrument-data-allotrope-example-1-vi-cell-blu-file | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of instrument-data-allotrope: Example 1: Vi-CELL BLU file (+2).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Example 1: Vi-CELL BLU file (+2) ## Example 1: Vi-CELL BLU file ``` User: "Convert this cell counting data to Allotrope format" [uploads viCell_Results.xlsx] Codex: 1. Detects Vi-CELL BLU (95% confidence) 2. Converts using allotropy native parser 3. Outputs: - viCell_Results_asm.json (full ASM) - viCell_Results_flat.csv (2D format) - viCell_parser.py (exportable code) ``` ## Example 2: Request for code handoff ``` User: "I need to give our data engineer code to parse NanoDrop files" Codex: 1. Generates self-contained Python script 2. Includes sample input/output 3. Documents all assumptions 4. Provides Jupyter notebook version ``` ## Example 3: LIMS-ready flattened output ``` User: "Convert this ELISA data to a CSV I can upload to our LIMS" Codex: 1. Parses plate reader data 2. Generates flattened CSV with columns: - sample_identifier, well_position, measurement_value, measurement_unit - instrument_serial_number, analysis_datetime, assay_type 3. Validates against common LIMS import requirements ```
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