Agent skill

Molecular Review Workflow

by aipoch in aipoch/medical-research-skills

Generates academic reviews for molecules in diseases using PubMed research.

MITAuto-check passedResearch & Science

Install Molecular Review Workflow

skills CLI
$ npx skills add aipoch/medical-research-skills --skill molecular-review-workflow -a claude-code

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

GitHub CLI
$ gh skill install aipoch/medical-research-skills molecular-review-workflow --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/Academic Writing/molecular-review-workflow' .claude/skills/molecular-review-workflow && 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
molecular-review-workflow
GitHub stars
1.9k
Token cost
~1.8k tokens
SKILL.md length
845 words
Files
3
Skills in repo
578
Repo updated
First seen
Licence
MIT

At a glance

Generates academic reviews for molecules in diseases using PubMed research.

  • Works in 4 steps: Confirm the user input, output path, and… → Edit the in-file CONFIG block or… → Run python scripts/pubmed_api.py with… → …
  • Needs biomedical literature review with Vancouver citation format
  • SKILL.md covers When to Use, Key Features, Dependencies and Example Usage, plus 16 more sections
  • Calls python; needs NCBI_API_KEY

What it does

Molecular Review Workflow is an agent skill from aipoch/medical-research-skills. Generates academic reviews for molecules in diseases using PubMed research. Invoke when user needs biomedical literature review with Vancouver citation format.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `POLISH_CHANGELOG.md` and `eval_report_molecular-review-workflow_result.json`).

It sits in Research & Science, covering Academic paper search, Literature review and Citation management. It works with PubMed and NCBI. 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

  • Needs biomedical literature review with Vancouver citation format
  • Tasks that involve Academic paper search
  • Tasks that involve Literature review

Example prompts

  • “Use the molecular-review-workflow skill to generate academic reviews for molecules in diseases using PubMed research”
  • “/molecular-review-workflow”

Requirements

  • Python 3
  • A credential in NCBI_API_KEY

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/pubmed_api.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

    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 these keys or tokens, usually read from environment variables:

    • NCBI_API_KEY

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

Context cost

Molecular Review Workflow loads about 1.8k tokens when it runs. Until then it costs about 46 tokens; SKILL.md has 845 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~46
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 845 words, ~1,794 tokens.

Download SKILL.mdSave it as .claude/skills/molecular-review-workflow/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
molecular-review-workflow
description
Generates academic reviews for molecules in diseases using PubMed research. Invoke when user needs biomedical literature review with Vancouver citation format.
license
MIT
author
AIPOCH

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

When to Use

  • Use this skill when the request matches its documented task boundary.
  • Use it when the user can provide the required inputs and expects a structured deliverable.
  • Prefer this skill for repeatable, checklist-driven execution rather than open-ended brainstorming.

Key Features

  • Scope-focused workflow aligned to: "Generates academic reviews for molecules in diseases using PubMed research. Invoke when user needs biomedical literature review with Vancouver citation format.".
  • Packaged executable path(s): scripts/pubmed_api.py plus 1 additional script(s).
  • Structured execution path designed to keep outputs consistent and reviewable.

Dependencies

  • Biopython library for PubMed API access
  • NCBI API credentials (NCBI_EMAIL and NCBI_API_KEY environment variables)

Example Usage

See ## Usage above for related details.

bash
cd "20260316/scientific-skills/Academic Writing/molecular-review-workflow"
python -m py_compile scripts/pubmed_api.py
python scripts/pubmed_api.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/pubmed_api.py with the validated inputs.
  4. Review the generated output and return the final artifact with any assumptions called out.

Implementation 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/pubmed_api.py with additional helper scripts under scripts/.
  • 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.

Validation Shortcut

Run this minimal command first to verify the supported execution path:

bash
python scripts/validate_skill.py --help

Molecular Review Workflow

This skill generates comprehensive academic reviews for specific molecules in disease contexts using PubMed research literature.

Inputs

  • disease: Disease name (required)
  • molecule: Molecule name (required)

Workflow Process

  1. Input Translation: Translates disease and molecule names to English
  2. Search Term Generation: Creates optimized PubMed search queries
  3. PubMed Search: Executes iterative PubMed searches using NCBI Entrez API
  4. Result Processing: Converts and formats search results
  5. Review Generation: Creates academic review with Vancouver citation format

Quality Rules

  • Citation numbering must start from 1 and increment sequentially
  • Citation numbers must match reference list entries
  • Review content must cover the molecule's role in the specified disease
  • Vancouver citation format must be used

Usage

Set environment variables:

bash
export NCBI_EMAIL="your-email@example.com"
export NCBI_API_KEY="your-ncbi-api-key"

Then invoke the skill with disease and molecule parameters.

When Not to Use

  • Do not use this skill when the required source data, identifiers, files, or credentials are missing.
  • Do not use this skill when the user asks for fabricated results, unsupported claims, or out-of-scope conclusions.
  • Do not use this skill when a simpler direct answer is more appropriate than the documented workflow.

Required Inputs

  • A clearly specified task goal aligned with the documented scope.
  • All required files, identifiers, parameters, or environment variables before execution.
  • Any domain constraints, formatting requirements, and expected output destination if applicable.
  1. Validate the request against the skill boundary and confirm all required inputs are present.
  2. Select the documented execution path and prefer the simplest supported command or procedure.
  3. Produce the expected output using the documented file format, schema, or narrative structure.
  4. Run a final validation pass for completeness, consistency, and safety before returning the result.
Show full SKILL.md (325 more words)Show less

Output Contract

  • Return a structured deliverable that is directly usable without reformatting.
  • If a file is produced, prefer a deterministic output name such as molecular_review_workflow_result.md unless the skill documentation defines a better convention.
  • Include a short validation summary describing what was checked, what assumptions were made, and any remaining limitations.

Validation and Safety Rules

  • Validate required inputs before execution and stop early when mandatory fields or files are missing.
  • Do not fabricate measurements, references, findings, or conclusions that are not supported by the provided source material.
  • Emit a clear warning when credentials, privacy constraints, safety boundaries, or unsupported requests affect the result.
  • Keep the output safe, reproducible, and within the documented scope at all times.

Failure Handling

  • If validation fails, explain the exact missing field, file, or parameter and show the minimum fix required.
  • If an external dependency or script fails, surface the command path, likely cause, and the next recovery step.
  • If partial output is returned, label it clearly and identify which checks could not be completed.

Input Validation

This skill accepts requests that match the documented purpose of molecular-review-workflow 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:

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

Quick Validation

Run this minimal verification path before full execution when possible:

bash
python scripts/pubmed_api.py --help

Expected output format:

text
Result file: molecular_review_workflow_result.md
Validation summary: PASS/FAIL with brief notes
Assumptions: explicit list if any

Deterministic Output Rules

  • Use the same section order for every supported request of this skill.
  • Keep output field names stable and do not rename documented keys across examples.
  • If a value is unavailable, emit an explicit placeholder instead of omitting the field.

Completion Checklist

  • Confirm all required inputs were present and valid.
  • Confirm the supported execution path completed without unresolved errors.
  • Confirm the final deliverable matches the documented format exactly.
  • Confirm assumptions, limitations, and warnings are surfaced explicitly.

© 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 2 other files in scientific-skills/Academic Writing/molecular-review-workflow of aipoch/medical-research-skills.

  • SKILL.md
  • POLISH_CHANGELOG.md
  • eval_report_molecular-review-workflow_result.json

Open the folder on GitHubat commit 686e09d

Compare with similar skills

Molecular Review Workflow 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.

Molecular Review Workflow compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Molecular Review Workflow this skillaipoch/medical-research-skills1.9k—~1.8kAutomated safety check: PassMIT
PubMed REST API Searchdavila7/claude-code-templates33k14 repos~3.9kAutomated safety check: PassMIT
Pubmed Databasejaechang-hits/SciAgent-Skills3741 repos~4.4kAutomated safety check: PassCC-BY-4.0
Literature Reviewneflibata-feng/MyArxiv-Agent12620 repos~5.9kAutomated safety check: NotesMIT
Academic Search and Citation RouterYuan1z0825/nature-skills47k—~884Automated safety check: PassApache-2.0
Literature ReviewK-Dense-AI/scientific-agent-skills48k1 repos~3.2kAutomated safety check: NotesMIT

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Works with

Questions about Molecular Review Workflow

What does Molecular Review Workflow do?

Generates academic reviews for molecules in diseases using PubMed research. Molecular Review Workflow is an agent skill from aipoch/medical-research-skills. Generates academic reviews for molecules in diseases using PubMed research.

When should I use Molecular Review Workflow?

Molecular Review Workflow fits situations like: needs biomedical literature review with Vancouver citation format; tasks that involve Academic paper search; tasks that involve Literature review.

How do I install Molecular Review Workflow in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill molecular-review-workflow -a claude-code`. Or copy the skill folder (scientific-skills/Academic Writing/molecular-review-workflow in aipoch/medical-research-skills) into .claude/skills/molecular-review-workflow in your project. Claude Code loads it when a task matches its description.

How do I install Molecular Review Workflow in Codex?

Run `npx skills add aipoch/medical-research-skills --skill molecular-review-workflow -a codex`. Or copy the skill folder (scientific-skills/Academic Writing/molecular-review-workflow in aipoch/medical-research-skills) into .agents/skills/molecular-review-workflow in your project. Codex loads it when a task matches its description.

Can I use Molecular Review Workflow 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 molecular-review-workflow -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/molecular-review-workflow, .gemini/skills/molecular-review-workflow, .github/skills/molecular-review-workflow and .opencode/skills/molecular-review-workflow in your project.

What does Molecular Review Workflow need to run?

Going by SKILL.md and its folder, Molecular Review Workflow needs the command-line tools its instructions call (python) and credentials named NCBI_API_KEY. Our summary lists: Python 3; A credential in NCBI_API_KEY.

Does Molecular Review Workflow 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 Molecular Review Workflow 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. Review the folder before installing.

What licence does Molecular Review Workflow use?

Molecular Review Workflow 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 Molecular Review Workflow use?

About 1.8k tokens (SKILL.md is roughly 7.2k 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 Molecular Review Workflow?

Skills that share tags, products or a category with Molecular Review Workflow: PubMed REST API Search (davila7/claude-code-templates, 33k stars), Pubmed Database (jaechang-hits/SciAgent-Skills, 374 stars), Literature Review (neflibata-feng/MyArxiv-Agent, 126 stars) and Academic Search and Citation Router (Yuan1z0825/nature-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Molecular Review Workflow?

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.