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Agent skill

Table 1 Generator Advanced

by aipoch in aipoch/medical-research-skills

Generate publication-ready baseline characteristics tables (Table 1) for clinical research papers with automatic variable type detection, appropriate statistics (mean±SD, median[IQR, n(%)), group…

MITAuto-check passedResearch & Science

Install Table 1 Generator Advanced

skills CLI
$ npx skills add aipoch/medical-research-skills --skill table-1-generator-advanced -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aipoch/medical-research-skills table-1-generator-advanced --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'scientific-skills/Data Analysis/table-1-generator-advanced' .claude/skills/table-1-generator-advanced && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
table-1-generator-advanced
GitHub stars
2k
Token cost
~1.6k tokens
SKILL.md length
675 words
Files
4 (incl. scripts)
Skills in repo
578
Repo updated
First seen
Licence
MIT

At a glance

Generate publication-ready baseline characteristics tables (Table 1) for clinical research papers with automatic variable type detection, appropriate statistics (mean±SD, median[IQR, n(%)), group…

  • Works in 6 steps: Load and validate data — Input: CSV file… → Identify grouping variable — Input:… → Select variables — Input: --vars list or… → …
  • Tasks that involve Clinical and healthcare research
  • SKILL.md covers Quick Check, Audit-Ready Commands, When to Use and Workflow, plus 13 more sections
  • Runs Python scripts from its folder; calls python

What it does

Table 1 Generator Advanced is an agent skill from aipoch/medical-research-skills. Generate publication-ready baseline characteristics tables (Table 1) for clinical research papers with automatic variable type detection, appropriate statistics (mean±SD, median[IQR, n(%)), group comparisons (t-test, chi-square), and APA formatting.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts (for example `POLISH_CHANGELOG.md`, `eval_report_table-1-generator-advanced_result.json` and `scripts/main.py`).

It sits in Research & Science, covering Clinical and healthcare research, Statistics and Data analysis. The repository describes itself as: Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing. The licence is MIT.

When your agent uses it

  • Tasks that involve Clinical and healthcare research
  • Tasks that involve Statistics
  • Tasks that involve Data analysis

Example prompts

  • “/table-1-generator-advanced”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Load and validate data — Input: CSV file path via --data → verify columns exist, check for missing values, detect data types…
  2. Identify grouping variable — Input: --group column name (e.g., treatment/control) → verify group balance → Output: group distribution…
  3. Select variables — Input: --vars list or auto-detect all eligible columns → classify each as continuous or categorical → Output: variable…
  4. Compute statistics — Continuous: mean±SD or median[IQR] (based on normality); Categorical: n(%); Group comparisons: t-test/chi-square → ⛔…
  5. Format Table 1 — Apply APA formatting, add p-values, footnotes for abbreviations → Output: --output CSV/Excel file
  6. Report missing data — Summarize missingness per variable, flag if >5% missing → Output: missing data appendix

What it can do on your machine

Read from SKILL.md and the folder at commit 686e09d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Table 1 Generator Advanced loads about 1.6k tokens when it runs. Until then it costs about 69 tokens; SKILL.md has 675 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~69
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 675 words, ~1,575 tokens.

Download SKILL.mdSave it as .claude/skills/table-1-generator-advanced/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
table-1-generator-advanced
description
Generate publication-ready baseline characteristics tables (Table 1) for clinical research papers with automatic variable type detection, appropriate statistics (mean±SD, median[IQR, n(%)), group comparisons (t-test, chi-square), and APA formatting.
license
MIT
author
AIPOCH

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

Table 1 Generator

Automated generation of baseline characteristics tables (Table 1) for clinical research papers.

Quick Check

Use this command to verify that the packaged script entry point can be parsed before deeper execution.

bash
python -m py_compile scripts/main.py

Audit-Ready Commands

Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.

bash
python -m py_compile scripts/main.py
python scripts/main.py --help

When to Use

Trigger phrases: "Table 1", "baseline characteristics", "demographic table", "clinical trial table", "summary statistics table"

  • Generating baseline characteristics tables (Table 1) for clinical research manuscripts
  • Comparing demographic and clinical variables across treatment groups
  • Creating summary statistics tables for clinical trial reports
  • Producing publication-ready tables with APA formatting

Workflow

  1. Load and validate data — Input: CSV file path via --data → verify columns exist, check for missing values, detect data types (continuous/categorical) → Output: data schema report
  2. Identify grouping variable — Input: --group column name (e.g., treatment/control) → verify group balance → Output: group distribution summary
  3. Select variables — Input: --vars list or auto-detect all eligible columns → classify each as continuous or categorical → Output: variable classification table
  4. Compute statistics — Continuous: mean±SD or median[IQR] (based on normality); Categorical: n(%); Group comparisons: t-test/chi-square → ⛔ Checkpoint: Confirm statistical method choices with user if normality is borderline → Output: statistics matrix
  5. Format Table 1 — Apply APA formatting, add p-values, footnotes for abbreviations → Output: --output CSV/Excel file
  6. Report missing data — Summarize missingness per variable, flag if >5% missing → Output: missing data appendix

Usage

text
python scripts/main.py --data patients.csv --group treatment --output table1.csv

Parameters

ParameterTypeRequiredDefaultDescription
--datastrYes-Patient data CSV file path
--groupstrNo-Grouping variable (e.g., treatment/control)
--varslist[str]No-Variables to include in the table
--outputstrYes-Output file path for Table 1

Features

  • Automatic variable type detection
  • Appropriate statistics (mean±SD, median[IQR], n(%))
  • Group comparisons (t-test, chi-square)
  • Missing data reporting
  • APA formatting

Output

  • Table 1 (CSV/Excel)
  • Statistical test results
  • Formatted for publication

Risk Assessment

Risk IndicatorAssessmentLevel
Code ExecutionPython/R scripts executed locallyMedium
Network AccessNo external API callsLow
File System AccessRead input files, write output filesMedium
Instruction TamperingStandard prompt guidelinesLow
Data ExposureOutput files saved to workspaceLow

Security Checklist

  • No hardcoded credentials or API keys
  • No unauthorized file system access (../)
  • Output does not expose sensitive information
  • Prompt injection protections in place
  • Input file paths validated (no ../ traversal)
  • Output directory restricted to workspace
  • Script execution in sandboxed environment
  • Error messages sanitized (no stack traces exposed)
  • Dependencies audited

Prerequisites

text
# Python dependencies
pip install -r requirements.txt

Evaluation Criteria

Success Metrics
  • Successfully executes main functionality
  • Output meets quality standards
  • Handles edge cases gracefully
  • Performance is acceptable
Show full SKILL.md (266 more words)Show less
Test Cases
  1. Basic Functionality: Standard input → Expected output
  2. Edge Case: Invalid input → Graceful error handling
  3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

  • Current Stage: Draft
  • Next Review Date: 2026-03-06
  • Known Issues: None
  • Planned Improvements:
    • Performance optimization
    • Additional feature support

Output Requirements

Every final response should make these items explicit when they are relevant:

  • Objective or requested deliverable
  • Inputs used and assumptions introduced
  • Workflow or decision path
  • Core result, recommendation, or artifact
  • Constraints, risks, caveats, or validation needs
  • Unresolved items and next-step checks

Error Handling

  • If required inputs are missing, state exactly which fields are missing and request only the minimum additional information.
  • If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment.
  • If scripts/main.py fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback.
  • Do not fabricate files, citations, data, search results, or execution outcomes.

Input Validation

This skill accepts requests that match the documented purpose of table-1-generator 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:

table-1-generator only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.

Response Template

Use the following fixed structure for non-trivial requests:

  1. Objective
  2. Inputs Received
  3. Assumptions
  4. Workflow
  5. Deliverable
  6. Risks and Limits
  7. Next Checks

If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.

© aipoch, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts) in scientific-skills/Data Analysis/table-1-generator-advanced of aipoch/medical-research-skills.

  • SKILL.md
  • POLISH_CHANGELOG.md
  • eval_report_table-1-generator-advanced_result.json
  • scripts/main.py

Open the folder on GitHubat commit 686e09d

Compare with similar skills

Table 1 Generator Advanced next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Table 1 Generator Advanced compared with similar skills
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Table 1 Generator Advanced this skillaipoch/medical-research-skills2k—~1.6kAutomated safety check: PassMIT
NeuroKit2 Biosignal Processingdavila7/claude-code-templates32k11 repos~3kAutomated safety check: PassMIT
Ukb Ppp Region FetchClawBio/ClawBio1.2k—~4.6kAutomated safety check: PassMIT
Bio Clinical Biostatistics Categorical TestsGPTomics/bioSkills1.2k2 repos~6.3kAutomated safety check: PassMIT
Bio Population Genetics Linkage DisequilibriumGPTomics/bioSkills1.2k1 repos~4.7kAutomated safety check: PassMIT
Statistical Data Analysislingzhi227/agent-research-skills386—~886Automated safety check: PassNone

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Categories

Questions about Table 1 Generator Advanced

What does Table 1 Generator Advanced do?

Generate publication-ready baseline characteristics tables (Table 1) for clinical research papers with automatic variable type detection, appropriate statistics (mean±SD, median[IQR, n(%)), group…. Table 1 Generator Advanced is an agent skill from aipoch/medical-research-skills. Generate publication-ready baseline characteristics tables (Table 1) for clinical research papers with automatic variable type detection, appropriate statistics (mean±SD, median[IQR, n(%)), group comparisons (t-test, chi-square), and APA formatting.

When should I use Table 1 Generator Advanced?

Table 1 Generator Advanced fits situations like: tasks that involve Clinical and healthcare research; tasks that involve Statistics; tasks that involve Data analysis.

How do I install Table 1 Generator Advanced in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill table-1-generator-advanced -a claude-code`. Or copy the skill folder (scientific-skills/Data Analysis/table-1-generator-advanced in aipoch/medical-research-skills) into .claude/skills/table-1-generator-advanced in your project. Claude Code loads it when a task matches its description.

How do I install Table 1 Generator Advanced in Codex?

Run `npx skills add aipoch/medical-research-skills --skill table-1-generator-advanced -a codex`. Or copy the skill folder (scientific-skills/Data Analysis/table-1-generator-advanced in aipoch/medical-research-skills) into .agents/skills/table-1-generator-advanced in your project. Codex loads it when a task matches its description.

Can I use Table 1 Generator Advanced in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aipoch/medical-research-skills --skill table-1-generator-advanced -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/table-1-generator-advanced, .gemini/skills/table-1-generator-advanced, .github/skills/table-1-generator-advanced and .opencode/skills/table-1-generator-advanced in your project.

What does Table 1 Generator Advanced need to run?

Going by SKILL.md and its folder, Table 1 Generator Advanced needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Table 1 Generator Advanced access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Table 1 Generator Advanced safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Table 1 Generator Advanced use?

Table 1 Generator Advanced is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Table 1 Generator Advanced use?

About 1.6k tokens (SKILL.md is roughly 6.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Table 1 Generator Advanced?

Skills that share tags, products or a category with Table 1 Generator Advanced: NeuroKit2 Biosignal Processing (davila7/claude-code-templates, 32k stars), Ukb Ppp Region Fetch (ClawBio/ClawBio, 1.2k stars), Bio Clinical Biostatistics Categorical Tests (GPTomics/bioSkills, 1.2k stars) and Bio Population Genetics Linkage Disequilibrium (GPTomics/bioSkills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Table 1 Generator Advanced?

aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,978 GitHub stars. The repository holds 578 skills in this directory. The repository was last updated on September 17, 2026.

Source: aipoch/medical-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.