journal-recommender

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.

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:

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.