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spreadsheet-ops

Spreadsheet processing and analysis for CSV/Excel; trigger when users ask to merge/clean tabular data, run statistics, add/edit Excel formulas, apply formatting, generate charts, or force workbook recalculation.

Install / Use

npx skills add aipoch/medical-research-skills --skill spreadsheet-ops

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

92/100

Supported Platforms

Universal

Our assessment of spreadsheet-ops

spreadsheet-ops scores 92/100 on our quality scale, 113th of 413 Data & Analytics skills we index (top 28%).

Its SKILL.md is 6.6 KB long, well organised into 18 sections with 6 code examples: a thorough specification that gives an agent plenty to work with.

With 1,916 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
20/20
Description
15/15
Adoption
14/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 12 days ago, so spreadsheet-ops is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-09-30. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

spreadsheet-ops compared with similar skills

All 4 of these similar skills score higher than spreadsheet-ops; compare them before choosing.

SkillScoreStarsUpdatedFormat
spreadsheet-ops (this skill)by aipoch921.9k12d agoSKILL.md
Agent-Reachby Panniantong10086.2k14d agoCLAUDE.md
algorithmic-artby anthropics100177.9k7d agoSKILL.md
pptxby anthropics100177.9k7d agoSKILL.md
designby nextlevelbuilder100130.2k8d agoSKILL.md

Frequently asked questions

How do I install spreadsheet-ops?
Run npx skills add aipoch/medical-research-skills --skill spreadsheet-ops. The install tabs above show the steps for each supported agent.
Which AI agents does spreadsheet-ops work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is spreadsheet-ops safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is spreadsheet-ops still maintained?
The repository was last updated 12 days ago, so spreadsheet-ops is actively maintained.

name: spreadsheet-ops description: Spreadsheet processing and analysis for CSV/Excel; trigger when users ask to merge/clean tabular data, run statistics, add/edit Excel formulas, apply formatting, generate charts, or force workbook recalculation. license: MIT author: AIPOCH

Source: https://github.com/aipoch/medical-research-skills

When to Use

  • You need to merge multiple CSV/Excel files into a single dataset and align columns.
  • You need to clean tabular data (normalize headers, deduplicate rows, resolve conflicts) before downstream use.
  • You need to perform data analysis/statistics on CSV/Excel (summaries, distributions, group-by metrics).
  • You need to add or edit formulas in an Excel workbook (including applying formulas across ranges).
  • You need to apply Excel formatting (including conditional formatting), generate charts, or force formula recalculation.

Key Features

  • CSV/Excel merge & cleaning: combine files, normalize column names, deduplicate, and resolve conflicts.
  • CSV/Excel analysis: compute descriptive statistics and analysis reports.
  • Excel-only formula operations: create/edit formulas and apply them to specified ranges.
  • Excel-only formatting: apply cell styles and conditional formatting rules.
  • Excel-only visualization: build charts from worksheet ranges.
  • Excel-only recalculation: set workbook to full recalculation (recalc flag) to ensure formulas update.

Dependencies

  • Python 3.x
  • Project Python dependencies are defined by the repository environment (e.g., requirements.txt / lockfile if present).
    (No explicit versions were provided in the source document.)

Example Usage

The following commands assume you are in the repository root and have a Python environment available.

1) Merge files (CSV/Excel)

python scripts/merge_files.py

2) Analyze data (CSV/Excel)

python scripts/analyze_data.py

3) Apply formulas (Excel only)

python scripts/apply_formulas.py

4) Apply formatting (Excel only)

python scripts/apply_formatting.py

5) Build charts (Excel only)

python scripts/build_charts.py

6) Force workbook recalculation (Excel only)

python scripts/recalc_workbook.py

Implementation Details

  • Workflow

    1. Confirm inputs/outputs: file paths, file formats (CSV vs Excel), worksheet names, and target ranges.
    2. Choose the task type: merge, analysis, formula, formatting, chart, or recalculation.
    3. Run the corresponding script and configure parameters in CONFIG (as used by the scripts).
    4. Produce output files and any generated reports.
  • Task boundaries

    • CSV/Excel supported: merging/cleaning, data analysis.
    • Excel only: formula creation/editing, formatting, chart visualization, and recalculation.
  • Key parameters to clarify (priority)

    • Input type: CSV or Excel; single file or multiple files.
    • Worksheet names and cell ranges to operate on (Excel).
    • Whether formulas/formatting/charts must preserve original styles.
    • Desired output format: CSV / Excel / JSON / Parquet.
  • Standards / constraints

    • Python file I/O must explicitly specify encoding='utf-8'.
    • json.dump(...) must set ensure_ascii=False.
  • Reference documentation (optional)

    • Column name matching & normalization: references/column-matching.md
    • Deduplication & conflict resolution: references/dedup-conflict.md
    • Large files & performance: references/large-files.md
    • Formula design & ranges: references/formulas.md
    • Formatting & conditional formatting: references/formatting.md
    • Data analysis & statistics: references/analysis.md
    • Charts & visualization: references/visualization.md
    • Formula recalculation: references/recalc.md

When Not to Use

  • Do not proceed when required input files, identifiers, parameters, or context are missing — ask the user to provide them first.
  • Do not assume capabilities beyond this skill's declared scope when the user requests external operations or inferences.
  • Do not proceed without user confirmation when overwriting existing results, executing high-cost batch operations, or expanding task scope.

Required Inputs

| Field | Required | Format/Source | Example | If Missing | |---|---|---|---|---| | User task description | Yes | Text | Research question, writing goal, analysis objective | Stop and ask user to provide | | Primary input material | Depends on task | Text, file path, ID, table, or literature | PMID, PDF, CSV, DOCX, keywords, etc. | Specify which material type is missing | | Output preference | No | Text | Language, format, target journal, template | Use skill default format |

Output Contract

  • Primary output: Structured result or target file aligned with this skill's objective.
  • Optional output: Intermediate check notes, issue list, supplementary suggestions, or generated file paths.
  • Format requirement: Unless the user specifies otherwise, prefer stable, reviewable Markdown or JSON; if the skill's bundled script requires a fixed format, use that format.
  • If partially complete: Must explicitly mark as PARTIAL and state which steps are completed and which remain.

Failure Handling

  • Missing critical input: Explicitly state which fields, files, or identifiers are missing and pause.
  • Script, template, or resource execution failure: Report the failing step, likely cause, and recovery suggestions — do not silently degrade.
  • Partial completion only: Return the verified portion first, then list remaining blockers and suggested next steps.

User Checkpoints

  • Before executing batch processing, overwriting files, long-running searches, or multi-stage generation, confirm scope and output format with the user.
  • Before proceeding when a key judgment is ambiguous, evidence is insufficient, or the workflow is entering the next stage, confirm with the user.

Input Validation

This skill accepts requests that match the documented purpose of spreadsheet-ops and include enough context to complete the workflow safely.

Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:

spreadsheet-ops only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.

Quick Validation

  • Check that key scripts, templates, or reference file paths this skill depends on exist.
  • Check that the final output contains the core fields, sections, or files specified for this task.
  • Check that results clearly mark assumptions, limitations, and incomplete items.

Related Skills

View on GitHub
GitHub Stars1.9k
CategoryData
Updated12d ago
Forks175

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions