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Agent skill

Clinical Study Info Extractor

by aipoch in aipoch/medical-research-skills

Batch extracts and verifies structured information (PMID, title, abstract, methodology, results, etc.) from clinical research literature using PMIDs.

MITAuto-check passedResearch & Science

Install Clinical Study Info Extractor

skills CLI
$ npx skills add aipoch/medical-research-skills --skill clinical-study-info-extractor -a claude-code

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

GitHub CLI
$ gh skill install aipoch/medical-research-skills clinical-study-info-extractor --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/Evidence Insight/clinical-study-info-extractor' .claude/skills/clinical-study-info-extractor && 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
clinical-study-info-extractor
GitHub stars
2k
Token cost
~1.2k tokens
SKILL.md length
555 words
Files
4 (incl. scripts, references)
Skills in repo
578
Repo updated
First seen
Licence
MIT

At a glance

Batch extracts and verifies structured information (PMID, title, abstract, methodology, results, etc.) from clinical research literature using PMIDs.

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

What it does

Clinical Study Info Extractor is an agent skill from aipoch/medical-research-skills. Batch extracts and verifies structured information (PMID, title, abstract, methodology, results, etc.) from clinical research literature using PMIDs. Use when the user wants to extract details from specific PMIDs.

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 `clinical-study-info-extractor_audit_result_v1.json`, `references/extraction_rules.md` and `scripts/utils.py`).

It sits in Research & Science, covering Clinical and healthcare research. 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 extract details from specific PMIDs
  • Tasks that involve Clinical and healthcare research

Example prompts

  • “/clinical-study-info-extractor”

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/utils.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

Clinical Study Info Extractor loads about 1.2k tokens when it runs, and up to ~1.6k if it reads all its reference files. Until then it costs about 61 tokens; SKILL.md has 555 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~61
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
~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). 555 words, ~1,209 tokens.

Download SKILL.mdSave it as .claude/skills/clinical-study-info-extractor/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
clinical-study-info-extractor
description
Batch extracts and verifies structured information (PMID, title, abstract, methodology, results, etc.) from clinical research literature using PMIDs. Use when the user wants to extract details from specific PMIDs.
license
MIT
author
AIPOCH

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

Clinical Study Info Extractor

This skill extracts structured information from clinical study literature based on provided PMIDs. It performs a search, parses the results, and uses LLM extraction with strict quality rules to produce a consolidated Markdown table.

When to Use

  • Use this skill when you need batch extracts and verifies structured information (pmid, title, abstract, methodology, results, etc.) from clinical research literature using pmids. use when the user wants to extract details from specific pmids in a reproducible workflow.
  • Use this skill when a evidence insight 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/utils.py is the most direct path to complete the request.
  • Use this skill when you need the clinical-study-info-extractor package behavior rather than a generic answer.

Key Features

  • Scope-focused workflow aligned to: Batch extracts and verifies structured information (PMID, title, abstract, methodology, results, etc.) from clinical research literature using PMIDs. Use when the user wants to extract details from specific PMIDs.
  • Packaged executable path(s): scripts/utils.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

See ## Usage above for related details.

bash
cd "20260316/scientific-skills/Evidence Insight/clinical-study-info-extractor"
python -m py_compile scripts/utils.py
python scripts/utils.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/utils.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/utils.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 (186 more words)Show less

Workflow

  1. Input Normalization: Splits and cleans the input string of PMIDs.
  2. Literature Search: Queries the PubMed API directly to fetch document details.
  3. Information Extraction: Iterates through documents to extract fields (Title, Year, Journal, Abstract, DOI, Type, Population, Sample Size, Intervention, Results, Conclusion).
  4. Verification: Enforces quality rules (e.g., sample size only for research articles).
  5. Output Formatting: Aggregates results into a Chinese Markdown table.

Usage

When you have a list of PMIDs and need structured details:

  1. Normalize Input: Use scripts/utils.py with normalize_pmids to parse the input string.

  2. Search & Process: Use scripts/utils.py with fetch_pubmed_data to query PubMed and get a list of document JSON strings.

  3. Extract & Verify: For each document, use the prompts defined in references/extraction_rules.md to extract and verify information.

    • Step 1: Extraction
    • Step 2: Verification

  4. Format Output: Use scripts/utils.py with format_table to generate the final Markdown table.

Quality Rules

See references/extraction_rules.md for detailed extraction logic and constraints.

  • Article Type: Must be one of Research, Meta-analysis, Case Report, Review.
  • Sample Size: Numeric only, empty for non-research.
  • Intervention: Single column, "None" if not mentioned.
  • Language: All Chinese except Journal Name.

© 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/Evidence Insight/clinical-study-info-extractor of aipoch/medical-research-skills.

  • SKILL.md
  • clinical-study-info-extractor_audit_result_v1.json
  • references/extraction_rules.md
  • scripts/utils.py

Open the folder on GitHubat commit 686e09d

Compare with similar skills

Clinical Study Info Extractor 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.

Clinical Study Info Extractor compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Clinical Study Info Extractor this skillaipoch/medical-research-skills2k—~1.2kAutomated safety check: PassMIT
Clinical Trials Databasegoogle-deepmind/science-skills3.2k2 repos~3.2kAutomated safety check: PassApache-2.0
CHARLS Paper Reproduction Guidexjtulyc/MedgeClaw6171 repos~1.8kAutomated safety check: PassNone
Biomedical Analysis Dispatchxjtulyc/MedgeClaw6171 repos~2kAutomated safety check: PassNone
Research Proposalluwill/research-skills858—~4.4kAutomated safety check: NotesNone
Medical Imaging ReviewLeonChaoX/qinyan-academic-skills9433 repos~1.1kAutomated safety check: NotesMIT

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Categories

Questions about Clinical Study Info Extractor

What does Clinical Study Info Extractor do?

Batch extracts and verifies structured information (PMID, title, abstract, methodology, results, etc.) from clinical research literature using PMIDs. Clinical Study Info Extractor is an agent skill from aipoch/medical-research-skills.) from clinical research literature using PMIDs.

When should I use Clinical Study Info Extractor?

Clinical Study Info Extractor fits situations like: the user wants to extract details from specific PMIDs; tasks that involve Clinical and healthcare research.

How do I install Clinical Study Info Extractor in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill clinical-study-info-extractor -a claude-code`. Or copy the skill folder (scientific-skills/Evidence Insight/clinical-study-info-extractor in aipoch/medical-research-skills) into .claude/skills/clinical-study-info-extractor in your project. Claude Code loads it when a task matches its description.

How do I install Clinical Study Info Extractor in Codex?

Run `npx skills add aipoch/medical-research-skills --skill clinical-study-info-extractor -a codex`. Or copy the skill folder (scientific-skills/Evidence Insight/clinical-study-info-extractor in aipoch/medical-research-skills) into .agents/skills/clinical-study-info-extractor in your project. Codex loads it when a task matches its description.

Can I use Clinical Study Info Extractor 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 clinical-study-info-extractor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/clinical-study-info-extractor, .gemini/skills/clinical-study-info-extractor, .github/skills/clinical-study-info-extractor and .opencode/skills/clinical-study-info-extractor in your project.

What does Clinical Study Info Extractor need to run?

Going by SKILL.md and its folder, Clinical Study Info Extractor needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Clinical Study Info Extractor 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 Clinical Study Info Extractor 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 Clinical Study Info Extractor use?

Clinical Study Info Extractor 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 Clinical Study Info Extractor use?

About 1.2k tokens (SKILL.md is roughly 4.8k 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 422 tokens, read only when the agent opens those files.

What are the alternatives to Clinical Study Info Extractor?

Skills that share tags, products or a category with Clinical Study Info Extractor: Clinical Trials Database (google-deepmind/science-skills, 3.2k stars), CHARLS Paper Reproduction Guide (xjtulyc/MedgeClaw, 617 stars), Biomedical Analysis Dispatch (xjtulyc/MedgeClaw, 617 stars) and Research Proposal (luwill/research-skills, 858 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Clinical Study Info Extractor?

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.