journal-recommender
Recommend academic journals based on manuscript topic, abstract, and impact factor expectations
Install / Use
npx skills add aipoch/medical-research-skills --skill journal-recommenderInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Education & ResearchSupported Platforms
Our assessment of journal-recommender
journal-recommender scores 88/100 on our quality scale, 154th of 357 Education & Research skills we index (top 44%).
Its SKILL.md is 5.9 KB long, well organised into 22 sections with 3 code examples: a thorough specification that gives an agent plenty to work with.
With 1,916 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 13 days ago, so journal-recommender is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
journal-recommender compared with similar skills
All 4 of these similar skills score higher than journal-recommender; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| journal-recommender (this skill)by aipoch | 88 | 1.9k | 13d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 86.4k | 15d ago | CLAUDE.md |
| last30days-skillby mvanhorn | 100 | 63.3k | today | CLAUDE.md |
| algorithmic-artby anthropics | 100 | 177.9k | 8d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 8d ago | SKILL.md |
Frequently asked questions
- How do I install journal-recommender?
- Run
npx skills add aipoch/medical-research-skills --skill journal-recommender. The install tabs above show the steps for each supported agent. - Which AI agents does journal-recommender work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is journal-recommender safe to use?
- It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is journal-recommender still maintained?
- The repository was last updated 13 days ago, so journal-recommender is actively maintained.
Skill content
View source on GitHubname: 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
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
-
Assess Manuscript:
- Analyze the provided
topicandabstract. - Extract keywords and determine the specific research field.
- Evaluate the workload and innovation of the study.
- Estimate the manuscript's potential Impact Factor (IF).
- Analyze the provided
-
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.
- Based on the assessment and the user's
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.mdunless 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:
python scripts/journal_ranker.py --help
Expected output format:
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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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
