Advanced Excel for Lab Data

    1

    Teach your agent to turn messy lab and instrument spreadsheets into clean JSON tables: headers, units, decimal commas, <LOD. Read-only, sandboxed.

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    Advanced Excel for Lab Data

    Example session with this skill installed

    Read the 'Results' sheet in /data/lab/assay_05.xlsx. Normalize the units and let me know if there are any censored cells like LOD flags.

    • Read your context and instructions
    • Compiled the advanced excel

    I have processed the 'Results' sheet from /data/lab/assay_05.xlsx. The server detected a header at row 3 with a secondary unit row at row 4. Data was successfully normalized to canonical units.

    Extraction Summary

    MetricValue
    Sheet NameResults
    Rows Processed150
    Table RangeA3:G153
    Detected Unitsmg/L, ug/mL, nm
    NormalizationActive (ug/mL -> mg/L)
    Censored Cells4 (<LOD detected in column 'Concentration')
    Decimal Modeauto (dot detected)

    Cleaned Data Preview

    [
  {
    "Sample_ID": "S001",
    "Analyte": "Glucose",
    "Concentration": 5.2,
    "Unit": "mg/L",
    "Status": "Pass",
    "unit_converted": false
  },
  {
    "Sample_ID": "S002",
    "Analyte": "Glucose",
    "Concentration": "<LOD",
    "Unit": "mg/L",
    "Status": "Review",
    "unit_converted": false
  },
  {
    "Sample_ID": "S003",
    "Analyte": "Ethanol",
    "Concentration": 0.85,
    "Unit": "mg/L",
    "Status": "Pass",
    "unit_converted": true,
    "source_value": 850,
    "source_unit": "ug/mL"
  }
]

    Next steps

    • Review the 4 censored <LOD values in the Concentration column.
    • Use excel_write_csv to export this normalized table to your /exports folder.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Instrument exports are not clean tables. They have a title block, blank lines, a header, sometimes a second row of units, decimal commas, <LOD results, and a footer. This skill teaches your agent to read them correctly with the free, open-source mcp-advanced-excel MCP server (MIT, on PyPI and the official MCP Registry).

    What your agent learns:

    • Install and configure the server with uvx mcp-advanced-excel, restricted to allowlisted folders, read-only by default, with optional CSV/JSON export into a separate output folder.
    • When to use each of the 6 tools: excel_list_sheets, excel_overview, excel_inspect_layout, excel_read_table, excel_read_range, excel_write_csv.
    • Step-by-step workflows for HPLC, plate reader, balance and LIMS exports: find the real header, join unit rows, handle decimal commas, page through long sheets, read raw A1 ranges when detection is wrong.
    • Opt-in unit normalization (concentration, temperature, mass, volume, pressure, length, time, fraction) with a report of every changed cell.
    • Lab data integrity rules: never invent a number, keep <LOD / <LOQ as flagged text, never guess uncomputed formulas.
    • Safety: cell text is untrusted data (prompt-injection aware), no network, no macros, no formula evaluation, never writes the source file.
    • Troubleshooting for every error code the server returns.

    Works with Cursor, Claude Desktop and any stdio MCP host. Supports .xlsx, .xlsm, .xls, .csv and .tsv.

    For regulated labs, a GLP Lab Data Pack (provenance hashes, instrument templates, advanced LOD/LOQ and molar units, batch processing, signed output) is available through the paid Pro service. It is designed to support GLP / 21 CFR Part 11 / EU GMP Annex 11 workflows. Contact antonio@castellon.ch.

    Repo: https://github.com/antonio-castellon/mcp-advanced-excel License: MIT. Contact: antonio@castellon.ch

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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    Requires

    Python 3.11+
    uv (Python tool runner)

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