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Agent skill

Roc Diagnostic Performance

by aipoch in aipoch/medical-research-skills

A skill your agent uses when evaluating diagnostic biomarker performance from case-control expression data with logistic regression and ROC curves, exporting coefficient and AUC tables together with…

MITAuto-check passedDocuments & Office

Install Roc Diagnostic Performance

skills CLI
$ npx skills add aipoch/medical-research-skills --skill roc-diagnostic-performance -a claude-code

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

GitHub CLI
$ gh skill install aipoch/medical-research-skills roc-diagnostic-performance --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/roc-diagnostic-performance' .claude/skills/roc-diagnostic-performance && 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
roc-diagnostic-performance
GitHub stars
2k
Token cost
~2.6k tokens
SKILL.md length
1,012 words
Files
24 (incl. scripts, references)
Skills in repo
578
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when evaluating diagnostic biomarker performance from case-control expression data with logistic regression and ROC curves, exporting coefficient and AUC tables together with…

  • Works in 5 steps: Validate Input → Prepare Analysis Dataset → Fit Logistic Regression → …
  • Evaluating diagnostic biomarker performance from case-control expression data with logistic regression and ROC curves
  • SKILL.md covers When to Use, When Not to Use, When to Read External Files and Usage, plus 9 more sections
  • Runs R scripts from its folder; calls bash

What it does

Roc Diagnostic Performance is an agent skill from aipoch/medical-research-skills. Use when evaluating diagnostic biomarker performance from case-control expression data with logistic regression and ROC curves, exporting coefficient and AUC tables together with a ROC PDF. NOT for: survival analysis, time-to-event outcomes, multiclass classification, calibration curves, decision-curve analysis, or nomogram construction.

Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 28 other files, including scripts and reference files (for example `eval_report_roc-diagnostic-performance_result.json`, `references/algorithm.md` and `references/cli-guide.md`).

It sits in Documents & Office, covering Performance reviews. 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

  • Evaluating diagnostic biomarker performance from case-control expression data with logistic regression and ROC curves
  • Exporting coefficient and AUC tables together with a ROC PDF

Example prompts

  • “/roc-diagnostic-performance”

Workflow steps

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

  1. Validate Input
  2. Prepare Analysis Dataset
  3. Fit Logistic Regression
  4. Compute ROC Performance
  5. Save Outputs

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 8 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

Roc Diagnostic Performance loads about 2.6k tokens when it runs, and up to ~4.8k if it reads all its reference files. Until then it costs about 92 tokens; SKILL.md has 1,012 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~92
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.8k

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). 1,012 words, ~2,631 tokens.

Download SKILL.mdSave it as .claude/skills/roc-diagnostic-performance/SKILL.md (or your agent's skills folder). This skill also uses 23 other files; get the full folder from GitHub.
name
roc-diagnostic-performance
description
Use when evaluating diagnostic biomarker performance from case-control expression data with logistic regression and ROC curves, exporting coefficient and AUC tables together with a ROC PDF. NOT for: survival analysis, time-to-event outcomes, multiclass classification, calibration curves, decision-curve analysis, or nomogram construction.

ROC Diagnostic Performance

When to Use

Use this skill when you need to:

  • evaluate one or more diagnostic marker genes in a case-control cohort;
  • build a multivariable logistic regression diagnostic model from marker expression values;
  • compare the ROC performance of the full model against individual markers.

Typical user requests:

  • "Use these genes to build a diagnostic ROC model for case vs control samples."
  • "Evaluate the AUC of FOXP3, CD45, and CD3E and plot all ROC curves together."
  • "Run logistic regression on biomarker expression and export ROC results."

When Not to Use

Do not use this skill for:

  • survival or prognostic analysis with time-to-event outcomes;
  • multiclass classification tasks;
  • calibration plots, nomograms, or decision-curve analysis;
  • non-expression diagnostic inputs such as imaging, clinical scores, or mutation-only tables.

When to Read External Files

SituationFile to ReadPurpose
Need algorithm detailsreferences/algorithm.mdLogistic regression, ROC, AUC, and modeling assumptions
Need to run analysisscripts/main.RExecute Rscript scripts/main.R --expression_file ... --group_file ...
Encounter errorsreferences/troubleshooting.mdCommon SKILL_* errors and solutions
Need CLI examplesreferences/cli-guide.mdDetailed command-line examples
Need test datatests/data/Example expression matrix and group file

Usage

bash
Rscript scripts/main.R \
  --expression_file ./expression_matrix.csv \
  --group_file ./group_info.csv \
  --marker_genes FOXP3,CD45,CD3E \
  --case_group Disease \
  --output_dir ./output/ \
  --seed 42

Arguments

ShortLongTypeDefaultDescription
-e--expression_filecharacterrequiredExpression matrix file in CSV/TSV format
-g--group_filecharacterrequiredGroup file with sample IDs and labels
-m--marker_genescharacterrequiredComma-separated marker genes
-c--case_groupcharacterrequiredCase group label in the group file
--group_colcharacterNULLOptional group column name; auto-detected if omitted
-o--output_dircharacter./output/Output directory
--overwriteflagFALSEAllow writing into a non-empty output directory
-s--seedinteger42Random seed for reproducibility
-T--timeout_secondsinteger0Elapsed time limit in seconds; 0 disables timeout
--plot_widthdouble6ROC plot width in inches
--plot_heightdouble6ROC plot height in inches
--font_familycharactersansPDF font family
--line_colorscharacter#E64B35,#4DBBD5,#00A087,#3C5488,#F39B7FComma-separated ROC line colors
--line_widthdouble1.2ROC curve line width
--show_diagonalcharactertrueShow diagonal reference line: true or false
--diagonal_colorcharacter#7F7F7FDiagonal line color
--diagonal_ltyinteger2Diagonal line type
--plot_titlecharacterROC Diagnostic PerformanceROC plot title
--x_labelcharacter1 - SpecificityX-axis label
--y_labelcharacterSensitivityY-axis label
--base_cexdouble0.9Base text-size multiplier
--legend_positioncharacterbottomrightLegend position
--legend_cexdouble0.8Legend text size

Input Format

Expression Matrix (expression_file)

CSV or TSV file with genes as rows and samples as columns. The first column must store unique gene identifiers.

csv
gene,Sample1,Sample2,Sample3
FOXP3,8.4,7.1,3.8
CD45,2.1,1.9,5.4
CD3E,5.8,6.2,4.0

Requirements

  • File extension must be .csv, .tsv, or .txt.
  • The first column must contain non-missing, unique gene identifiers.
  • Remaining columns must be sample IDs.
  • Selected marker genes must have numeric finite expression values across matched samples.
Group File (group_file)

CSV or TSV file with sample IDs in the first column and at least one group-label column.

csv
sample,group
Sample1,Disease
Sample2,Disease
Sample3,Control

Requirements

  • File extension must be .csv, .tsv, or .txt.
  • The first column must contain non-missing, unique sample IDs.
  • At least one group column must be present.
  • The case_group value must appear in the selected group column.
  • At least 10 matched samples, 2 case samples, and 2 control samples are required.

Output Files

FileDescription
data/analysis_data.rdsMatched sample-level analysis dataset used for model fitting
data/roc_model.rdsSaved logistic regression model bundle with data and selected genes
table/model_coefficients.csvLogistic regression coefficients, z statistics, p-values, and odds ratios
table/roc_auc_summary.csvAUC values for the full model and each marker
plot/roc_curve.pdfROC curves for the full model and individual markers
session_info.txtSession information and run parameters
model_coefficients.csv
ColumnDescription
termModel term name
estimateLogistic regression coefficient
std_errorStandard error of the coefficient
z_valueWald z statistic
p_valueWald test p-value
odds_ratioExponentiated coefficient
odds_ratio_95_ciOdds ratio with 95% confidence interval
roc_auc_summary.csv
ColumnDescription
modelFull model or marker name
aucArea under the ROC curve
Show full SKILL.md (405 more words)Show less

Workflow

Step 1: Validate Input
  • Check that the expression matrix and group file exist and have supported formats.
  • Validate unique gene identifiers and sample IDs.
  • Match samples shared by both files.
Step 2: Prepare Analysis Dataset
  • Keep only the requested marker genes that exist in the expression matrix.
  • Merge matched expression values with group labels.
  • Convert the selected case group to binary outcome labels.
Step 3: Fit Logistic Regression
  • Fit a multivariable logistic regression model using the selected markers.
  • Extract coefficient estimates, standard errors, p-values, and odds ratios.
Step 4: Compute ROC Performance
  • Generate the ROC curve of the full logistic model.
  • Generate ROC curves for each individual marker.
  • Calculate AUC values for the full model and each marker.
Step 5: Save Outputs
  • Save the matched analysis dataset and model bundle as .rds files.
  • Save coefficient and AUC summary tables as .csv files.
  • Save the combined ROC plot as a PDF.

Examples

Basic Usage
bash
Rscript scripts/main.R \
  -e expression_matrix.csv \
  -g group_info.csv \
  -m FOXP3,CD45,CD3E \
  -c Disease \
  -o ./output/
With Explicit Group Column and Custom Plot
bash
Rscript scripts/main.R \
  -e expression_matrix.csv \
  -g group_info.csv \
  -m FOXP3,CD45,CD3E \
  -c Disease \
  --group_col diagnosis \
  --plot_width 8 \
  --plot_height 6 \
  --plot_title "Biomarker ROC Comparison" \
  --legend_position topright \
  -o ./output/
With Test Data
bash
Rscript scripts/main.R \
  -e tests/data/sample_expression_matrix.csv \
  -g tests/data/sample_group_info.csv \
  -m FOXP3,CD45,CD3E \
  -c Disease \
  -o tests/expected_output/ \
  --overwrite

Error Handling

ErrorCauseSolution
SKILL_INVALID_PARAMETERMissing required argument, invalid option value, invalid matrix/group structure, invalid case label, insufficient case-control counts, or logistic fitting failureCheck argument names, input content, class balance, and model stability
SKILL_FILE_NOT_FOUNDInput file does not existVerify the file path
SKILL_EMPTY_DATAInput file contains no usable rows, or no requested markers remain after filteringCheck file content, delimiter, and marker names
SKILL_MISSING_COLUMNSRequested group column is absentVerify --group_col and the group file header
SKILL_SAMPLE_MISMATCHExpression matrix and group file do not share sample IDsVerify that sample IDs match exactly between files
SKILL_PACKAGE_NOT_FOUNDRequired R package is not installedInstall the missing CRAN package

IF error persists, READ: references/troubleshooting.md

Testing

Smoke Test With Included Data
bash
Rscript scripts/main.R --help

Rscript scripts/main.R \
  -e tests/data/sample_expression_matrix.csv \
  -g tests/data/sample_group_info.csv \
  -m FOXP3,CD45,CD3E \
  -c Disease \
  -o tests/expected_output/ \
  --overwrite
Automated Smoke Test Script
bash
Rscript tests/run_smoke_test.R

Optional shell wrapper:

bash
bash tests/run_smoke_test.sh
Expected Output
text
tests/expected_output/
|-- data/analysis_data.rds
|-- data/roc_model.rds
|-- plot/roc_curve.pdf
|-- session_info.txt
|-- table/model_coefficients.csv
`-- table/roc_auc_summary.csv

References

  1. Hosmer DW, Lemeshow S, Sturdivant RX (2013). Applied Logistic Regression.
  2. Fawcett T (2006). An Introduction to ROC Analysis. Pattern Recognition Letters.
  3. Robin X et al. (2011). pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics.

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: 2026-04-17 | Version: 2.1.0

© 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 23 other files (scripts, references) in awesome-med-research-skills/Data Analysis/roc-diagnostic-performance of aipoch/medical-research-skills.

  • SKILL.md
  • eval_report_roc-diagnostic-performance_result.json
  • references/algorithm.md
  • references/cli-guide.md
  • references/troubleshooting.md
  • scripts/cli.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_expression_matrix.csv
  • tests/data/sample_group_info.csv
  • tests/expected_output/data
  • … and 8 more

Open the folder on GitHubat commit 686e09d

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Categories

Questions about Roc Diagnostic Performance

What does Roc Diagnostic Performance do?

A skill your agent uses when evaluating diagnostic biomarker performance from case-control expression data with logistic regression and ROC curves, exporting coefficient and AUC tables together with…. Roc Diagnostic Performance is an agent skill from aipoch/medical-research-skills. Use when evaluating diagnostic biomarker performance from case-control expression data with logistic regression and ROC curves, exporting coefficient and AUC tables together with a ROC PDF.

When should I use Roc Diagnostic Performance?

Roc Diagnostic Performance fits situations like: evaluating diagnostic biomarker performance from case-control expression data with logistic regression and ROC curves; exporting coefficient and AUC tables together with a ROC PDF.

How do I install Roc Diagnostic Performance in Claude Code?

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

How do I install Roc Diagnostic Performance in Codex?

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

Can I use Roc Diagnostic Performance 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 roc-diagnostic-performance -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/roc-diagnostic-performance, .gemini/skills/roc-diagnostic-performance, .github/skills/roc-diagnostic-performance and .opencode/skills/roc-diagnostic-performance in your project.

What does Roc Diagnostic Performance need to run?

Going by SKILL.md and its folder, Roc Diagnostic Performance needs R for the scripts in its folder and the command-line tools its instructions call (bash).

Does Roc Diagnostic Performance 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 Roc Diagnostic Performance 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 Roc Diagnostic Performance use?

Roc Diagnostic Performance 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 Roc Diagnostic Performance use?

About 2.6k 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 2.1k tokens, read only when the agent opens those files.

What are the alternatives to Roc Diagnostic Performance?

Skills that share tags, products or a category with Roc Diagnostic Performance: HTML Ppt Xhs White Editorial (nexu-io/open-design, 100k stars), Mathmodel Skill (handsomeZR-netizen/mathmodel-skill, 292 stars), Power Design (ItsssssJack/power-design, 722 stars) and Paginated Report (data-goblin/power-bi-agentic-development, 1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Roc Diagnostic Performance?

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.