Agent skill

Quapas Quality Assessment For Prognosis Studies

by aipoch in aipoch/medical-research-skills

Evaluates bias in medical literature (prognosis studies) using QUAPAS criteria.

MITAuto-check passedData & Analytics

Install Quapas Quality Assessment For Prognosis Studies

skills CLI
$ npx skills add aipoch/medical-research-skills --skill quapas-quality-assessment-for-prognosis-studies -a claude-code

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

GitHub CLI
$ gh skill install aipoch/medical-research-skills quapas-quality-assessment-for-prognosis-studies --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/quapas-quality-assessment-for-prognosis-studies' .claude/skills/quapas-quality-assessment-for-prognosis-studies && 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
quapas-quality-assessment-for-prognosis-studies
GitHub stars
1.9k
Token cost
~1.2k tokens
SKILL.md length
562 words
Files
4 (incl. scripts, references)
Skills in repo
578
Repo updated
First seen
Licence
MIT

At a glance

Evaluates bias in medical literature (prognosis studies) using QUAPAS criteria.

  • Works in 4 steps: Confirm the user input, output path, and… → Edit the in-file CONFIG block or… → Run python scripts/extract_pdf.py with… → …
  • The user wants to assess the quality
  • SKILL.md covers When to Use, Key Features, Dependencies and Example Usage, plus 5 more sections
  • Runs Python scripts from its folder; calls python

What it does

Quapas Quality Assessment For Prognosis Studies is an agent skill from aipoch/medical-research-skills. Evaluates bias in medical literature (prognosis studies) using QUAPAS criteria. Use when the user wants to assess the quality or risk of bias of a medical paper text.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `quapas-quality-assessment-for-prognosis-studies_audit_result_v1.json`, `references/quapas_prompts.md` and `scripts/extract_pdf.py`).

It sits in Data & Analytics, covering 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

  • The user wants to assess the quality
  • Risk of bias of a medical paper text

Example prompts

  • “Use the quapas-quality-assessment-for-prognosis-studies skill to evaluate bias in medical literature (prognosis studies) using QUAPAS criteria”
  • “/quapas-quality-assessment-for-prognosis-studies”

Requirements

  • Python 3

Workflow steps

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

  1. Confirm the user input, output path, and any required config values.
  2. Edit the in-file CONFIG block or documented parameters if the script uses fixed settings.
  3. Run python scripts/extract_pdf.py with the validated inputs.
  4. Review the generated output and return the final artifact with any assumptions called out.

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

Quapas Quality Assessment For Prognosis Studies loads about 1.2k tokens when it runs, and up to ~2.8k if it reads all its reference files. Until then it costs about 54 tokens; SKILL.md has 562 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~54
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.8k

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). 562 words, ~1,214 tokens.

Download SKILL.mdSave it as .claude/skills/quapas-quality-assessment-for-prognosis-studies/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
quapas-quality-assessment-for-prognosis-studies
description
Evaluates bias in medical literature (prognosis studies) using QUAPAS criteria. Use when the user wants to assess the quality or risk of bias of a medical paper text.
license
MIT
author
AIPOCH

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

QUAPAS Bias Evaluator

When to Use

  • Use this skill when you need evaluates bias in medical literature (prognosis studies) using quapas criteria. use when the user wants to assess the quality or risk of bias of a medical paper text in a reproducible workflow.
  • Use this skill when a data analytics task needs a packaged method instead of ad-hoc freeform output.
  • Use this skill when the user expects a concrete deliverable, validation step, or file-based result.
  • Use this skill when scripts/extract_pdf.py is the most direct path to complete the request.
  • Use this skill when you need the quapas-quality-assessment for prognosis studies package behavior rather than a generic answer.

Key Features

  • Scope-focused workflow aligned to: Evaluates bias in medical literature (prognosis studies) using QUAPAS criteria. Use when the user wants to assess the quality or risk of bias of a medical paper text.
  • Packaged executable path(s): scripts/extract_pdf.py.
  • Reference material available in references/ for task-specific guidance.
  • Structured execution path designed to keep outputs consistent and reviewable.

Dependencies

  • Python: 3.10+. Repository baseline for current packaged skills.
  • Third-party packages: not explicitly version-pinned in this skill package. Add pinned versions if this skill needs stricter environment control.

Example Usage

bash
cd "20260316/scientific-skills/Data Analytics/quapas-quality-assessment-for-prognosis-studies"
python -m py_compile scripts/extract_pdf.py
python scripts/extract_pdf.py --help

Example run plan:

  1. Confirm the user input, output path, and any required config values.
  2. Edit the in-file CONFIG block or documented parameters if the script uses fixed settings.
  3. Run python scripts/extract_pdf.py with the validated inputs.
  4. Review the generated output and return the final artifact with any assumptions called out.

Implementation Details

See ## Workflow above for related details.

  • Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
  • Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
  • Primary implementation surface: scripts/extract_pdf.py.
  • Reference guidance: references/ contains supporting rules, prompts, or checklists.
  • Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
  • Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.
Show full SKILL.md (233 more words)Show less

Description

This skill evaluates the risk of bias in prognosis studies using the Quality of Prognosis Studies (QUAPAS) tool. It analyzes 5 domains: Participants, Index Test, Outcome, Flow and Timing, and Analysis.

Workflow

  1. Input: The user provides the full text of a medical paper.

  2. Study Extraction:

    • Extract the first author's name and year (e.g., "Wang, 2018").
  3. Domain Analysis: For each of the 5 domains, analyze the text using the questions defined in references/quapas_prompts.md.

    • Domain 1: Participants
    • Domain 2: Index Test
    • Domain 3: Outcome
    • Domain 4: Flow and Timing
    • Domain 5: Analysis
  4. Risk of Bias (ROB) Assessment: For each domain, determine the Risk of Bias (Low, High, Unclear) based on the answers to the signaling questions:

    • If all answers are "Yes" -> Low Risk.
    • If any answer is "No" -> High Risk.
    • If information is missing -> Unclear.
  5. Overall Judgment: Determine the overall risk of bias for the study based on the domain results.

    • If most domains are Low Risk -> Low Overall Bias.
    • If key domains are High Risk -> High Overall Bias.
  6. Final Output: Generate a JSON object strictly following the schema below:

    json
    {
      "study": "Author, Year",
      "D1": "Low|High|Unclear",
      "D2": "Low|High|Unclear",
      "D3": "Low|High|Unclear",
      "D4": "Low|High|Unclear",
      "D5": "Low|High|Unclear",
      "overall": "Low|High|Unclear"
    }

References

Helper Scripts

PDF Text Extraction

When the user provides a PDF file path, use extract_pdf.py to extract the text content before assessment:

© 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, references) in scientific-skills/Data Analysis/quapas-quality-assessment-for-prognosis-studies of aipoch/medical-research-skills.

  • SKILL.md
  • quapas-quality-assessment-for-prognosis-studies_audit_result_v1.json
  • references/quapas_prompts.md
  • scripts/extract_pdf.py

Open the folder on GitHubat commit 686e09d

Compare with similar skills

Quapas Quality Assessment For Prognosis Studies 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.

Quapas Quality Assessment For Prognosis Studies compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Quapas Quality Assessment For Prognosis Studies this skillaipoch/medical-research-skills1.9k—~1.2kAutomated safety check: PassMIT
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Exploratory Data AnalysisOleafly/Oleafly2122 repos~3.4kAutomated safety check: NotesMIT
Raccoon DataanalysisSenseTime-Copilot/raccoon-dataanalysis-skill137—~1.9kAutomated safety check: PassNone
CSV Data Analysis5zjk5/prompt-engineering127—~2.6kAutomated safety check: PassNone
Data Analysiszj-unicom-ai/UniEmployee360—~857Automated safety check: PassMIT

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Questions about Quapas Quality Assessment For Prognosis Studies

What does Quapas Quality Assessment For Prognosis Studies do?

Evaluates bias in medical literature (prognosis studies) using QUAPAS criteria. Quapas Quality Assessment For Prognosis Studies is an agent skill from aipoch/medical-research-skills. Evaluates bias in medical literature (prognosis studies) using QUAPAS criteria.

When should I use Quapas Quality Assessment For Prognosis Studies?

Quapas Quality Assessment For Prognosis Studies fits situations like: the user wants to assess the quality; risk of bias of a medical paper text.

How do I install Quapas Quality Assessment For Prognosis Studies in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill quapas-quality-assessment-for-prognosis-studies -a claude-code`. Or copy the skill folder (scientific-skills/Data Analysis/quapas-quality-assessment-for-prognosis-studies in aipoch/medical-research-skills) into .claude/skills/quapas-quality-assessment-for-prognosis-studies in your project. Claude Code loads it when a task matches its description.

How do I install Quapas Quality Assessment For Prognosis Studies in Codex?

Run `npx skills add aipoch/medical-research-skills --skill quapas-quality-assessment-for-prognosis-studies -a codex`. Or copy the skill folder (scientific-skills/Data Analysis/quapas-quality-assessment-for-prognosis-studies in aipoch/medical-research-skills) into .agents/skills/quapas-quality-assessment-for-prognosis-studies in your project. Codex loads it when a task matches its description.

Can I use Quapas Quality Assessment For Prognosis Studies 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 quapas-quality-assessment-for-prognosis-studies -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/quapas-quality-assessment-for-prognosis-studies, .gemini/skills/quapas-quality-assessment-for-prognosis-studies, .github/skills/quapas-quality-assessment-for-prognosis-studies and .opencode/skills/quapas-quality-assessment-for-prognosis-studies in your project.

What does Quapas Quality Assessment For Prognosis Studies need to run?

Going by SKILL.md and its folder, Quapas Quality Assessment For Prognosis Studies needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Quapas Quality Assessment For Prognosis Studies 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 Quapas Quality Assessment For Prognosis Studies 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 Quapas Quality Assessment For Prognosis Studies use?

Quapas Quality Assessment For Prognosis Studies 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 Quapas Quality Assessment For Prognosis Studies use?

About 1.2k tokens (SKILL.md is roughly 4.9k 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 1.6k tokens, read only when the agent opens those files.

What are the alternatives to Quapas Quality Assessment For Prognosis Studies?

Skills that share tags, products or a category with Quapas Quality Assessment For Prognosis Studies: Excel and CSV Data Analysis (bytedance/deer-flow, 84k stars), Exploratory Data Analysis (Oleafly/Oleafly, 212 stars), Raccoon Dataanalysis (SenseTime-Copilot/raccoon-dataanalysis-skill, 137 stars) and CSV Data Analysis (5zjk5/prompt-engineering, 127 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Quapas Quality Assessment For Prognosis Studies?

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.