Agent skill

Univariate Multivariable Cox Regression

by aipoch in aipoch/medical-research-skills

Install Univariate Multivariable Cox Regression

skills CLI

$ npx skills add aipoch/medical-research-skills --skill univariate-multivariable-cox-regression -a claude-code

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

GitHub CLI

$ gh skill install aipoch/medical-research-skills univariate-multivariable-cox-regression --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/'awesome-med-research-skills/Data Analysis/univariate-multivariable-cox-regression' .claude/skills/univariate-multivariable-cox-regression && 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/

Paste into Claude Code

Install the "univariate-multivariable-cox-regression" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/univariate-multivariable-cox-regression into .claude/skills/univariate-multivariable-cox-regression/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "univariate-multivariable-cox-regression", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/univariate-multivariable-cox-regression

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add aipoch/medical-research-skills --skill univariate-multivariable-cox-regression -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install aipoch/medical-research-skills univariate-multivariable-cox-regression --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/'awesome-med-research-skills/Data Analysis/univariate-multivariable-cox-regression' .agents/skills/univariate-multivariable-cox-regression && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "univariate-multivariable-cox-regression" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/univariate-multivariable-cox-regression into .agents/skills/univariate-multivariable-cox-regression/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "univariate-multivariable-cox-regression", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add aipoch/medical-research-skills --skill univariate-multivariable-cox-regression -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install aipoch/medical-research-skills univariate-multivariable-cox-regression --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/'awesome-med-research-skills/Data Analysis/univariate-multivariable-cox-regression' .cursor/skills/univariate-multivariable-cox-regression && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "univariate-multivariable-cox-regression" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/univariate-multivariable-cox-regression into .cursor/skills/univariate-multivariable-cox-regression/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "univariate-multivariable-cox-regression", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/aipoch/medical-research-skills.git --path 'awesome-med-research-skills/Data Analysis/univariate-multivariable-cox-regression'

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add aipoch/medical-research-skills --skill univariate-multivariable-cox-regression -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install aipoch/medical-research-skills univariate-multivariable-cox-regression --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/'awesome-med-research-skills/Data Analysis/univariate-multivariable-cox-regression' .gemini/skills/univariate-multivariable-cox-regression && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "univariate-multivariable-cox-regression" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/univariate-multivariable-cox-regression into .gemini/skills/univariate-multivariable-cox-regression/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "univariate-multivariable-cox-regression", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install aipoch/medical-research-skills univariate-multivariable-cox-regression

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add aipoch/medical-research-skills --skill univariate-multivariable-cox-regression -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/'awesome-med-research-skills/Data Analysis/univariate-multivariable-cox-regression' .github/skills/univariate-multivariable-cox-regression && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "univariate-multivariable-cox-regression" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/univariate-multivariable-cox-regression into .github/skills/univariate-multivariable-cox-regression/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "univariate-multivariable-cox-regression", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add aipoch/medical-research-skills --skill univariate-multivariable-cox-regression -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install aipoch/medical-research-skills univariate-multivariable-cox-regression --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/'awesome-med-research-skills/Data Analysis/univariate-multivariable-cox-regression' .opencode/skills/univariate-multivariable-cox-regression && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "univariate-multivariable-cox-regression" agent skill from https://github.com/aipoch/medical-research-skills/tree/main/awesome-med-research-skills/Data%20Analysis/univariate-multivariable-cox-regression into .opencode/skills/univariate-multivariable-cox-regression/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "univariate-multivariable-cox-regression", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: univariate-multivariable-cox-regression
GitHub stars: 1.9k
Token cost: ~2.7k tokens
SKILL.md length: 941 words
Files: 25 (incl. scripts, references)
Skills in repo: 578
Repo updated: Sep 17, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Works in 7 steps: Run Cox Analysis → Generate Univariate Forest Plot → Generate Multivariable Forest Plot → …
Export result tables
SKILL.md covers When to Use, When Not to Use, When to Read External Files and Usage, plus 7 more sections
Runs R scripts from its folder; calls bash

What it does

Univariate Multivariable Cox Regression is an agent skill from aipoch/medical-research-skills. Use when running prognostic survival analysis on a clinical cohort with time-to-event data to estimate univariate and multivariable Cox proportional hazards models, export result tables, and generate forest plots. NOT for: nomogram construction, calibration curves, time-dependent ROC analysis, or model training/feature selection beyond the built-in univariate screening rule.

Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 29 other files, including scripts and reference files (for example `eval_report_univariate-multivariable-cox-regression_result.json`, `references/algorithm.md` and `references/cli-guide.md`).

It sits in Data & Analytics, covering Machine learning, Performance reviews and Fine-tuning. 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

Export result tables
Generate forest plots

Example prompts

“/univariate-multivariable-cox-regression”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

Run Cox Analysis
Generate Univariate Forest Plot
Generate Multivariable Forest Plot
Validate and Prepare Data
Run Univariate Cox Models
Run Multivariable Cox Model
Generate Forest Plots

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 9 files in scripts/ (R, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
- bash
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

Univariate Multivariable Cox Regression loads about 2.7k tokens when it runs, and up to ~5.7k if it reads all its reference files. Until then it costs about 104 tokens; SKILL.md has 941 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~104
When it runs · the whole SKILL.md, loaded when a task matches: ~2.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~5.7k

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). 941 words, ~2,709 tokens.

Download SKILL.mdSave it as .claude/skills/univariate-multivariable-cox-regression/SKILL.md (or your agent's skills folder). This skill also uses 24 other files; get the full folder from GitHub.

name: univariate-multivariable-cox-regression
description: Use when running prognostic survival analysis on a clinical cohort with time-to-event data to estimate univariate and multivariable Cox proportional hazards models, export result tables, and generate forest plots. NOT for: nomogram construction, calibration curves, time-dependent ROC analysis, or model training/feature selection beyond the built-in univariate screening rule.

Univariate and Multivariable Cox Regression

When to Use

Use this skill when you need to:

run univariate and multivariable Cox regression on a clinical survival cohort;
identify prognostic clinical variables associated with time-to-event outcomes;
export hazard-ratio tables and then render forest plots from those results.

Typical user requests:

"Run single-factor and multi-factor Cox regression on this survival dataset."
"Find prognostic variables from my clinical cohort and give me forest plots."
"Use futime and fustat to do Cox regression for age, stage, and risk."

When Not to Use

Do not use this skill for:

nomogram construction or calibration analysis;
time-dependent ROC analysis or external prognostic model validation;
feature discovery pipelines beyond the built-in univariate screening rule;
non-survival outcomes such as binary diagnosis or differential expression.

When to Read External Files

Situation	File to Read	Purpose
Need algorithm details	`references/algorithm.md`	Statistical workflow, assumptions, and feature-selection rule
Need to run analysis	`scripts/main.R`	Execute `Rscript scripts/main.R <command> [options]`
Encounter errors	`references/troubleshooting.md`	Common `SKILL_*` errors and fixes
Need CLI examples	`references/cli-guide.md`	Command-specific argument examples
Need test data	`tests/data/`	Minimal runnable cohort for smoke testing

Usage

1. Run Cox Analysis

bash

Rscript scripts/main.R analyze \
  --data_file ./clinical_data.csv \
  --features age,gender,stage,risk \
  --time_col futime \
  --event_col fustat \
  --output_dir ./output/ \
  --seed 42

2. Generate Univariate Forest Plot

bash

Rscript scripts/main.R forest-plot \
  --data_file ./output/table/prognosis_uni_cox_results.xlsx \
  --plot_save ./output/plot/uni_forest_plot.pdf

3. Generate Multivariable Forest Plot

bash

Rscript scripts/main.R multi-forest-plot \
  --data_file ./output/table/prognosis_multi_cox_results.xlsx \
  --plot_save ./output/plot/multi_forest_plot.pdf

Arguments

Analyze Command

Short	Long	Type	Default	Description
`-d`	`--data_file`	character	required	Clinical CSV file with sample IDs as row names
`-f`	`--features`	character	`age,gender,stage,Tstage,Nstage,Mstage,risk`	Comma-separated features for Cox analysis
`-t`	`--time_col`	character	`futime`	Survival time column
`-e`	`--event_col`	character	`fustat`	Event column encoded as `1=event`, `0=censored`
`-u`	`--skip_univariate`	character	`false`	Skip univariate screening and fit multivariable model on all requested features
`-o`	`--output_dir`	character	`./output/`	Output directory
	`--overwrite`	flag	`FALSE`	Allow writing into a non-empty output directory
`-s`	`--seed`	integer	`42`	Random seed for reproducibility
`-T`	`--timeout_seconds`	integer	`0`	Elapsed time limit in seconds; `0` disables timeout

Forest Plot Commands

These arguments apply to both forest-plot and multi-forest-plot.

Short	Long	Type	Default	Description
`-d`	`--data_file`	character	required	Cox result table in `.xlsx`, `.xls`, or `.csv` format
`-p`	`--plot_save`	character	required	Output PDF path
`-w`	`--width`	double	`8`	Plot width in inches
`-H`	`--height`	double	`6`	Plot height in inches
`-F`	`--font_size`	double	`11`	Font size for forest-plot labels
`-s`	`--seed`	integer	`42`	Random seed for reproducibility
`-T`	`--timeout_seconds`	integer	`0`	Elapsed time limit in seconds; `0` disables timeout

Input Format

Clinical Data (`--data_file` for `analyze`)

CSV file with sample IDs as row names and one column per feature/end-point variable.

csv

",age,gender,stage,futime,fustat,risk
SAMPLE_001,65,Male,StageIII,365,1,high
SAMPLE_002,52,Female,StageII,730,0,low
SAMPLE_003,78,Male,StageIV,180,1,high

Requirements

The file must be CSV.
Sample IDs must be stored in the first column as row names.
time_col must contain finite numeric values greater than 0.
event_col must contain only 0 and 1.
All requested features, time_col, and event_col must exist.
At least 10 complete samples and at least 2 events are required after filtering incomplete rows.

Cox Result Table (`--data_file` for plot commands)

The plotting commands read the output table created by analyze.

Required columns:

Characteristics
Total(N)
HR (95% CI)
P value

Output Files

Analyze Command

File	Description
`table/prognosis_uni_cox_results.xlsx`	Univariate Cox result table. Present unless `--skip_univariate true`
`table/prognosis_multi_cox_results.xlsx`	Multivariable Cox result table
`data/analysis_data.rds`	Serialized complete-case dataset used for Cox fitting
`session_info.txt`	Session info and recorded run parameters

Plot Commands

File	Description
`plot/uni_forest_plot.pdf`	PDF forest plot generated by `forest-plot`
`plot/multi_forest_plot.pdf`	PDF forest plot generated by `multi-forest-plot`
`plot/session_info.txt`	Session info and plotting parameters written beside the PDF

Show full SKILL.md (400 more words)Show less

Result Table Columns

Column	Description
`Characteristics`	Variable name for continuous terms, or level label for categorical terms
`Total(N)`	Number of complete-case samples used for modeling
`HR (95% CI)`	Hazard ratio with 95% confidence interval
`P value`	Wald-test p-value formatted to three decimals or `<0.001`
`feature`	Source feature corresponding to each row

Workflow

Step 1: Validate and Prepare Data

Read the clinical CSV.
Check required columns and data types.
Convert character predictors to factors.
Remove rows with missing values across requested model variables.

Step 2: Run Univariate Cox Models

Fit one Cox model per feature when --skip_univariate false.
Export hazard ratios, confidence intervals, and p-values.

Step 3: Run Multivariable Cox Model

Use all significant univariate features with p < 0.05.
If fewer than 3 significant features are found, fall back to all requested features.
Export adjusted hazard ratios, confidence intervals, and p-values.

Step 4: Generate Forest Plots

Read the result table.
Parse HR (95% CI) values.
Render a one-page PDF forest plot.

Examples

Basic Analysis

bash

Rscript scripts/main.R analyze \
  -d tests/data/sample_clinical_survival_data.csv \
  -o tests/expected_output/ \
  --overwrite

Analysis With Selected Features and Overwrite

bash

Rscript scripts/main.R analyze \
  -d clinical_data.csv \
  -f age,gender,stage,risk \
  -o ./results/ \
  --overwrite \
  -T 600

Direct Multivariable Fit Without Univariate Screening

bash

Rscript scripts/main.R analyze \
  -d clinical_data.csv \
  -f age,stage,risk \
  -u true \
  -o ./results/

Plot Generation

bash

Rscript scripts/main.R forest-plot \
  -d ./results/table/prognosis_uni_cox_results.xlsx \
  -p ./results/plot/uni_forest_plot.pdf \
  -w 10 -H 7 -F 12

Rscript scripts/main.R multi-forest-plot \
  -d ./results/table/prognosis_multi_cox_results.xlsx \
  -p ./results/plot/multi_forest_plot.pdf \
  -w 10 -H 7 -F 12

Error Handling

Error	Cause	Solution
`SKILL_INVALID_PARAMETER`	Missing required CLI value, invalid extension, unknown command, unreadable CSV input, invalid clinical values, too few complete samples/events, or Cox model fitting failure caused by unsupported input data	Check argument names, file types, clinical value constraints, and model input suitability
`SKILL_FILE_NOT_FOUND`	Input file path does not exist	Verify the input path
`SKILL_MISSING_COLUMNS`	Required columns are absent from the clinical file or plot table	Check column names and spelling
`SKILL_EMPTY_DATA`	Input file or plot table contains no usable rows	Verify file content and export process
`SKILL_PACKAGE_NOT_FOUND`	Required R package is missing	Install the listed CRAN package(s)

IF error persists, READ: references/troubleshooting.md

Testing

Smoke Test With Included Data

bash

Rscript scripts/main.R --help

Rscript scripts/main.R analyze \
  -d tests/data/sample_clinical_survival_data.csv \
  -o tests/expected_output/ \
  --overwrite

Rscript scripts/main.R forest-plot \
  -d tests/expected_output/table/prognosis_uni_cox_results.xlsx \
  -p tests/expected_output/plot/uni_forest_plot.pdf

Rscript scripts/main.R multi-forest-plot \
  -d tests/expected_output/table/prognosis_multi_cox_results.xlsx \
  -p tests/expected_output/plot/multi_forest_plot.pdf

Automated Smoke Test Script

bash

Rscript tests/run_smoke_test.R

Optional shell wrapper:

bash

bash tests/run_smoke_test.sh

Expected Outputs

text

tests/expected_output/
|-- data/analysis_data.rds
|-- plot/multi_forest_plot.pdf
|-- plot/session_info.txt
|-- plot/uni_forest_plot.pdf
|-- session_info.txt
|-- table/prognosis_multi_cox_results.xlsx
`-- table/prognosis_uni_cox_results.xlsx

References

Cox DR (1972). Regression Models and Life-Tables. Journal of the Royal Statistical Society: Series B.
Therneau TM, Grambsch PM (2000). Modeling Survival Data: Extending the Cox Model.
Harrell FE (2015). Regression Modeling Strategies.

For detailed algorithm, READ: references/algorithm.md

Implementation Checklist

CLI parsing with optparse
set.seed() for reproducibility
requireNamespace() dependency checks
Session info recording
Timeout parameter exposed as CLI option
File reading instructions in SKILL.md
Modular script structure in scripts/
Test data provided in tests/data/
Error handling with SKILL_* codes
References documented in references/

Last updated: 2026-04-16 | Version: 1.1.0

Files

SKILL.md and 24 other files (scripts, references) in awesome-med-research-skills/Data Analysis/univariate-multivariable-cox-regression of aipoch/medical-research-skills.

SKILL.md
eval_report_univariate-multivariable-cox-regression_result.json
references/algorithm.md
references/cli-guide.md
references/troubleshooting.md
scripts/cli.R
scripts/cox_helpers.R
scripts/functions.R
scripts/io.R
scripts/main.R
scripts/plotting.R
scripts/run_analysis.R
scripts/utils.R
scripts/validation.R
tests/data/sample_clinical_survival_data.csv
tests/expected_output/data
… and 9 more

Open the folder on GitHubat commit 686e09d

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Questions about Univariate Multivariable Cox Regression

What does Univariate Multivariable Cox Regression do?

A skill your agent uses when running prognostic survival analysis on a clinical cohort with time-to-event data to estimate univariate and multivariable Cox proportional hazards models, export result…. Univariate Multivariable Cox Regression is an agent skill from aipoch/medical-research-skills. Use when running prognostic survival analysis on a clinical cohort with time-to-event data to estimate univariate and multivariable Cox proportional hazards models, export result tables, and generate forest plots.

When should I use Univariate Multivariable Cox Regression?

Univariate Multivariable Cox Regression fits situations like: export result tables; generate forest plots.

How do I install Univariate Multivariable Cox Regression in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill univariate-multivariable-cox-regression -a claude-code`. Or copy the skill folder (awesome-med-research-skills/Data Analysis/univariate-multivariable-cox-regression in aipoch/medical-research-skills) into .claude/skills/univariate-multivariable-cox-regression in your project. Claude Code loads it when a task matches its description.

How do I install Univariate Multivariable Cox Regression in Codex?

Run `npx skills add aipoch/medical-research-skills --skill univariate-multivariable-cox-regression -a codex`. Or copy the skill folder (awesome-med-research-skills/Data Analysis/univariate-multivariable-cox-regression in aipoch/medical-research-skills) into .agents/skills/univariate-multivariable-cox-regression in your project. Codex loads it when a task matches its description.

Can I use Univariate Multivariable Cox Regression 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 univariate-multivariable-cox-regression -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/univariate-multivariable-cox-regression, .gemini/skills/univariate-multivariable-cox-regression, .github/skills/univariate-multivariable-cox-regression and .opencode/skills/univariate-multivariable-cox-regression in your project.

What does Univariate Multivariable Cox Regression need to run?

Going by SKILL.md and its folder, Univariate Multivariable Cox Regression needs R for the scripts in its folder and the command-line tools its instructions call (bash).

Does Univariate Multivariable Cox Regression 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 Univariate Multivariable Cox Regression 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 Univariate Multivariable Cox Regression use?

Univariate Multivariable Cox Regression is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Univariate Multivariable Cox Regression use?

About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.9k tokens, read only when the agent opens those files.

What are the alternatives to Univariate Multivariable Cox Regression?

Skills that share tags, products or a category with Univariate Multivariable Cox Regression: Geoml (italo-goncalves/geoML, 109 stars), Evaluating Machine Learning Models (foryourhealth111-pixel/Vibe-Skills, 3.6k stars), Bio Machine Learning Survival Analysis (GPTomics/bioSkills, 1.2k stars) and Mlnet (managedcode/dotnet-skills, 486 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Univariate Multivariable Cox Regression?

aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,937 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.

Install Univariate Multivariable Cox Regression

Facts

At a glance

What it does

When your agent uses it

Example prompts

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Univariate and Multivariable Cox Regression

When to Use

When Not to Use

When to Read External Files

Usage

1. Run Cox Analysis

2. Generate Univariate Forest Plot

3. Generate Multivariable Forest Plot

Arguments

Analyze Command

Forest Plot Commands

Input Format

Clinical Data (--data_file for analyze)

Cox Result Table (--data_file for plot commands)

Output Files

Analyze Command

Plot Commands

Result Table Columns

Workflow

Step 1: Validate and Prepare Data

Step 2: Run Univariate Cox Models

Step 3: Run Multivariable Cox Model

Step 4: Generate Forest Plots

Examples

Basic Analysis

Analysis With Selected Features and Overwrite

Direct Multivariable Fit Without Univariate Screening

Plot Generation

Error Handling

Testing

Smoke Test With Included Data

Automated Smoke Test Script

Expected Outputs

References

Implementation Checklist

Files

Compare with similar skills

Similar skills

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Related

Questions about Univariate Multivariable Cox Regression

Clinical Data (`--data_file` for `analyze`)

Cox Result Table (`--data_file` for plot commands)