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Agent skill

Journal Recommender

by aipoch in aipoch/medical-research-skills

Recommend academic journals based on manuscript topic, abstract, and impact factor expectations.

MITAuto-check passed

Install Journal Recommender

skills CLI
$ npx skills add aipoch/medical-research-skills --skill journal-recommender -a claude-code

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

GitHub CLI
$ gh skill install aipoch/medical-research-skills journal-recommender --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/Other/journal-recommender .claude/skills/journal-recommender && 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
journal-recommender
GitHub stars
2k
Token cost
~1.5k tokens
SKILL.md length
587 words
Files
4 (incl. scripts)
Skills in repo
567
Repo updated
First seen
Licence
MIT

At a glance

Recommend academic journals based on manuscript topic, abstract, and impact factor expectations.

  • Works in 2 steps: Assess Manuscript → Recommend Journals
  • The user wants to find suitable journals for their research manuscript
  • SKILL.md covers Output Format, Overview, Workflow and Usage, plus 9 more sections
  • Runs Python scripts from its folder; calls python

What it does

Journal Recommender is an agent skill from aipoch/medical-research-skills. Recommend academic journals based on manuscript topic, abstract, and impact factor expectations. Use when the user wants to find suitable journals for their research manuscript, especially when they provide a topic, abstract, and target Impact Factor.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts (for example `POLISH_CHANGELOG.md`, `eval_report_journal-recommender_result.json` and `scripts/journal_ranker.py`).

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 find suitable journals for their research manuscript
  • Especially when they provide a topic
  • Target Impact Factor

Example prompts

  • “/journal-recommender”

Requirements

  • Python 3

Workflow steps

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

  1. Assess Manuscript
  2. Recommend Journals

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

Journal Recommender loads about 1.5k tokens when it runs. Until then it costs about 68 tokens; SKILL.md has 587 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~68
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

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). 587 words, ~1,518 tokens.

Download SKILL.mdSave it as .claude/skills/journal-recommender/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
journal-recommender
description
Recommend academic journals based on manuscript topic, abstract, and impact factor expectations. Use when the user wants to find suitable journals for their research manuscript, especially when they provide a topic, abstract, and target Impact Factor.
license
MIT
author
AIPOCH

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

Output Format

All recommendations must follow the three-tier table format below. Each tier must recommend at least 5 journals.

## Journal Recommendation Report

### Recommendation Overview
| Tier | Count | Strategy |
|---------|:------:|---------|
| Sprint | N | Impact factor higher than target, requires some luck |
| Robust | N | Impact factor matches target, higher hit rate |
| Safe | N | Impact factor lower than target, near-certain acceptance |

### Sprint Journals
| Journal | Impact Factor | Review Period | Acceptance Rate | Match Reason | Warning Risk |
|-------|:-------:|:--------:|:-----:|---------|:--------:|
| Nature | 64.8 | 3-6 months | ~8% | High topic match | Safe |

### Robust Journals
| Journal | Impact Factor | Review Period | Acceptance Rate | Match Reason | Warning Risk |
|-------|:-------:|:--------:|:-----:|---------|:--------:|

### Safe Journals
| Journal | Impact Factor | Review Period | Acceptance Rate | Match Reason | Warning Risk |
|-------|:-------:|:--------:|:-----:|---------|:--------:|

### Warning Notes
List any journals on the warning list to avoid submitting to.

Journal Recommender

Overview

This skill analyzes a research manuscript (topic, abstract, and optional full text) to extract key information (keywords, field, workload, innovation) and recommends journals in three categories: Sprint (High), Robust (Match), and Safe (Low).

Workflow

  1. Assess Manuscript:

    • Analyze the provided topic and abstract.
    • Extract keywords and determine the specific research field.
    • Evaluate the workload and innovation of the study.
    • Estimate the manuscript's potential Impact Factor (IF).

  2. Recommend Journals:

    • Based on the assessment and the user's target_if, search for and recommend journals.
    • Categorize recommendations into:
      • Sprint Journals: IF slightly higher than target (max +5).
      • Robust Journals: IF matches the target and assessment.
      • Safe Journals: IF lower than target, ensuring high acceptance chance.
    • Ensure at least 5 journals per category.
    • Constraint: Do not recommend journals from the CAS warning list.

Usage

Inputs
  • topic (Required): The title or topic of the manuscript.
  • abstract (Required): The abstract of the manuscript.
  • target_if (Required): The expected Impact Factor (number).
  • manuscript (Optional): Full text of the manuscript.
  • article_type (Default: "research article"): Type of the article.
Deterministic Operations
  • Sorting: The recommended journals are sorted by Impact Factor in descending order using scripts/journal_ranker.py.

Quality Rules

  • IF Sorting: Journals must be strictly sorted by IF.
  • Safety: No CAS warning journals are allowed.
  • Quantity: Minimum 5 journals per category.

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.

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.
Show full SKILL.md (227 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 journal_recommender_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.

Quick Validation

Run this minimal verification path before full execution when possible:

bash
python scripts/journal_ranker.py --help

Expected output format:

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

User Checkpoints

  • Before executing batch processing, overwriting files, long-running searches, or multi-stage generation, confirm scope and output format with the user.
  • Before proceeding when a key judgment is ambiguous, evidence is insufficient, or the workflow is entering the next stage, confirm with the user.

© 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) in scientific-skills/Other/journal-recommender of aipoch/medical-research-skills.

  • SKILL.md
  • POLISH_CHANGELOG.md
  • eval_report_journal-recommender_result.json
  • scripts/journal_ranker.py

Open the folder on GitHubat commit 686e09d

Compare with similar skills

Journal Recommender 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.

Journal Recommender compared with similar skills
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Journal Recommender this skillaipoch/medical-research-skills2k—~1.5kAutomated safety check: PassMIT
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Abstractbrycewang-stanford/Auto-Empirical-Research-Skills4.5k—~495Automated safety check: NotesCustom licence
Recommendagenticnotetaking/arscontexta3.5k1 repos~5.1kAutomated safety check: PassMIT
AbstractionEpicenterHQ/epicenter4.8k—~445Automated safety check: PassCustom licence
Restaurant Recommendationsasgeirtj/system_prompts_leaks69k—~755Automated safety check: PassCC0-1.0

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Questions about Journal Recommender

What does Journal Recommender do?

Recommend academic journals based on manuscript topic, abstract, and impact factor expectations. Journal Recommender is an agent skill from aipoch/medical-research-skills. Recommend academic journals based on manuscript topic, abstract, and impact factor expectations.

When should I use Journal Recommender?

Journal Recommender fits situations like: the user wants to find suitable journals for their research manuscript; especially when they provide a topic; target Impact Factor.

How do I install Journal Recommender in Claude Code?

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

How do I install Journal Recommender in Codex?

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

Can I use Journal Recommender 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 journal-recommender -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/journal-recommender, .gemini/skills/journal-recommender, .github/skills/journal-recommender and .opencode/skills/journal-recommender in your project.

What does Journal Recommender need to run?

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

Does Journal Recommender 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 Journal Recommender 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 Journal Recommender use?

Journal Recommender 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 Journal Recommender use?

About 1.5k tokens (SKILL.md is roughly 6.1k 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 Journal Recommender?

Skills that share tags, products or a category with Journal Recommender: Content Topic Recommender (XBuilderLAB/cheat-on-content, 7.2k stars), Abstract (brycewang-stanford/Auto-Empirical-Research-Skills, 4.5k stars), Recommend (agenticnotetaking/arscontexta, 3.5k stars) and Abstraction (EpicenterHQ/epicenter, 4.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Journal Recommender?

aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,974 GitHub stars. The repository holds 567 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.