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.
Scanned 9/6/2026
Install to Claude Code
npx -y skills add aipoch/medical-research-skills --skill journal-recommender --agent claude-codeInstalls into .claude/skills of the current project.
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---
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](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.
## 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.
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