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journal-recommender

Recommend academic journals in three tiers based on manuscript topic, abstract, and target impact factor.

Updated Sep 15, 2026
Search Tags:#research#academic publishing#impact factor#manuscript submission#journal ranking#journal recommendation
One-click install
npx skills add https://github.com/mrsonord2240/openscience-specialists --skill journal-recommender-mrsonord2240
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: journal-recommender
Source: https://github.com/mrsonord2240/openscience-specialists/tree/main/specialists/manuscript-revision-specialist/versions/1.0.0/package/skills/journal-recommender
Command: npx skills add https://github.com/mrsonord2240/openscience-specialists --skill journal-recommender-mrsonord2240

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve? Choosing where to submit a research manuscript is time-consuming and risky: authors must match their topic and study quality against hundreds of journals while avoiding predatory or warning-listed outlets. This Skill analyzes a manuscript's topic and abstract and produces a structured three-tier journal recommendation report. ## Core Features & Use Cases - Three-Tier Recommendations: Generates Sprint (higher IF), Robust (matching IF), and Safe (lower IF) journal lists with at least 5 journals per tier, including review period, acceptance rate, and match reasoning. - Impact Factor Sorting: Uses a deterministic Python script to rank candidate journals by impact factor in descending order. - Safety Filtering: Excludes journals on the CAS warning list and flags warning risks in the output table. - Use Case: A researcher with a completed abstract and a target impact factor of 5 receives a formatted report of 15+ candidate journals split across sprint, robust, and safe tiers, ready for submission planning. ## Quick Start Ask the assistant to recommend journals for your manuscript by providing the topic, abstract, and a target impact factor such as 5.

Frequently Asked Questions about journal-recommender

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I find suitable journals for my research manuscript?▼

Provide your manuscript topic, abstract, and a target impact factor. The skill assesses keywords, field, workload, and innovation, then returns at least 5 journals each in sprint, robust, and safe tiers with match reasons and risk warnings.

How are journal recommendations ranked by impact factor?▼

Candidate journals are parsed and sorted by impact factor in descending order using the scripts/journal_ranker.py Python script. This deterministic ranking ensures the highest-impact options appear first within each recommendation tier.

Does the journal recommendation exclude predatory or warning-listed journals?▼

Yes, journals on the CAS warning list are explicitly excluded from all recommendations. The output report also includes a warning notes section listing any journals to avoid submitting to.

What inputs are required to get journal recommendations?▼

Three inputs are required: the manuscript topic or title, the abstract, and a numeric target impact factor. Optionally you can provide the full manuscript text and article type, which defaults to research article.

What are the limitations of impact factor based journal selection?▼

Impact factor alone does not guarantee acceptance or fit; scope alignment, article type, and editorial preferences also matter. This skill addresses this partly through match reasoning and tiered risk levels, but final decisions should include manual scope review.

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