Paper Submission Evaluator

SkillDev tools

Lets your agent read an academic paper, score its novelty, and recommend 20 target journals with ABS star ratings.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Paper Submission Evaluator skill

About this capability

Evaluate a paper's contribution novelty, identify best-fit SSCI journal fields and ABS star rating, and recommend 20 target journals. Trigger when user says "paper submission" / "paper-submission" / "投稿评估" / "期刊推荐" / "target journal" / "选刊".

What this skill tells your AI

The instructions your AI receives, as published by brycewang-stanford/auto-empirical-research-skills in skills/67-econfin-workflow-toolkit/paper-submission/SKILL.md and read by ahel’s review.

Overview

This skill evaluates an academic paper and produces a comprehensive submission target report. It performs four assessments:

  1. Contribution Novelty Score (0-100): How much the paper advances existing literature, assessed via web search for related work.
  2. Best-Fit SSCI Journal Fields: Which ABS field categories best match the paper.
  3. Appropriate ABS Star Rating: What star level (1, 2, 3, 4, 4*) the paper's quality warrants.
  4. Top 20 Journal Recommendations: From the 2 best-fitting fields, at the recommended ABS star level, list 20 SSCI-indexed journals with rationale.

The ABS journal list is read from C:\Users\Admin\.claude\skills\paper-submission\asset\Business School Journal List 2023.pdf (referred to as AJG2025). This file is bundled with the skill in the asset/ folder, so it is always available regardless of changes to the user's desktop.

The final report is saved as target.pdf in the paper's directory.

Workflow

Phase 1: Initialization

  1. Receive paper path from user (via $ARGUMENTS or ask). Accept either:
    • A PDF file containing the full paper
    • A project folder containing LaTeX files (main.tex, tables, etc.)
  2. Read the paper thoroughly:
    • For PDF: Read all pages using the Read tool with page ranges.
    • For LaTeX project: Read main.tex and key result files.
  3. Extract key information and record internally:
    • Research question / hypothesis
    • Methodology (empirical strategy, identification, data)
    • Data source and sample (country, market, time period)
    • Key findings (baseline results, mechanisms, heterogeneity)
    • Stated or implied contributions
    • Keywords and JEL codes (if present)
  4. Summarize the paper in ~200 words for use in subsequent phases. Present this summary to the user for confirmation:
    我已阅读论文,以下是摘要:
    
    研究问题:[...]
    方法:[...]
    数据:[...]
    主要发现:[...]
    贡献方向:[...]
    
    请确认以上理解是否正确,或进行调整。
    
  5. Wait for user confirmation before proceeding.

Phase 2: Literature Novelty Assessment (Web Search Required)

This phase evaluates how novel the paper's contribution is relative to existing literature. Web search is mandatory.

Step 2a: Identify Search Dimensions

Based on the paper summary, identify 3-5 search dimensions that capture the paper's core novelty claims. Each dimension represents a facet of the paper's contribution. Examples:

  • Topic novelty: "Has [X effect on Y] been studied before?"
  • Methodological novelty: "Has [identification strategy Z] been applied to [this question]?"
  • Data novelty: "Has [this data source / market / country] been used for [this question]?"
  • Mechanism novelty: "Have [these channels] been documented?"
  • Setting novelty: "Has [this policy / institutional context] been exploited?"
Step 2b: Conduct Web Searches

For each dimension, conduct at least 2 targeted web searches using WebSearch. Search queries should be in English and target academic literature. Example queries:

  • "[dependent variable]" AND "[independent variable]" site:ssrn.com OR site:nber.org
  • "[key mechanism]" AND "[research context]" journal article
  • [topic keywords] survey OR review OR meta-analysis

For each search:

  1. Execute the WebSearch query.
  2. Read the top results using WebFetch to check abstracts and findings.
  3. Record: (a) how many closely related papers exist, (b) how the current paper differs from them, (c) whether the core finding has been documented before.
Step 2c: Score the Contribution

Assign a novelty score out of 100 based on these criteria:

Score RangeMeaningCriteria
85-100Highly novelNo prior paper addresses this exact question with this approach. Opens a new research direction.
70-84Substantially novelFew prior papers on a similar topic, but this paper offers a clearly distinct angle (new data, new mechanism, new identification).
55-69Moderately novelTopic has been studied, but this paper contributes incremental insights (new setting, additional robustness, extension of known results).
40-54Limited noveltyMultiple papers have addressed similar questions with similar methods. Contribution is primarily confirmatory or extends to a new sample.
0-39Low noveltyThe main findings have been well-documented. Contribution is marginal.

For each dimension, assign a sub-score and weight. The final score is the weighted average.

Present the assessment to the user:

文献创新性评估结果:

维度1: [dimension name] — 子分 [X]/100
  已有文献:[list 2-3 most relevant prior papers with year]
  本文区别:[how this paper differs]

维度2: [dimension name] — 子分 [X]/100
  ...

综合创新性得分:[SCORE]/100
评级:[Highly novel / Substantially novel / Moderately novel / Limited novelty / Low novelty]

主要创新点:
1. [innovation point 1]
2. [innovation point 2]
3. [innovation point 3]

潜在风险:
- [e.g., "Reviewer may argue that [X] has been shown by [Author, Year]"]

Phase 3: Field Matching and ABS Star Rating

Step 3a: Identify Best-Fit Fields

The ABS journal list uses these field categories (22 fields total):

  • ACCOUNT (Accounting)
  • FINANCE (Finance)
  • ECON (Economics)
  • STRAT (Strategy)
  • MKT (Marketing)
  • OPS&TECH (Operations and Technology)
  • OR&MANSCI (Operations Research and Management Science)
  • ORG STUD (Organization Studies)
  • HRM&EMP (Human Resource Management and Employment)
  • IB&AREA (International Business and Area Studies)
  • INNOV (Innovation)
  • PUB SEC (Public Sector Management)
  • SOC SCI (Social Sciences)
  • SECTOR (Sector Studies)
  • BUS & ECON HIST (Business and Economic History)
  • MDEV&EDU (Management Development and Education)
  • REGIONAL (Regional Studies)
  • ENT-SBM (Entrepreneurship and Small Business Management)
  • ETHICS-CSR-MAN (Ethics, CSR and Management)
  • INFO MAN (Information Management)
  • PSYCH (GENERAL) (Psychology - General)
  • PSYCH (WOP-OB) (Psychology - Work and Organizational)

Based on the paper's topic, methodology, and data, identify the 2 most suitable fields. Consider:

  • What is the paper's primary disciplinary home? (e.g., corporate finance paper → FINANCE)
  • What is a strong secondary field? (e.g., uses accounting data → ACCOUNT; studies innovation → INNOV)
  • Where would the paper's contribution resonate most?
Step 3b: Determine Appropriate ABS Star Rating

Assess the paper's quality level to determine the appropriate ABS star tier for targeting:

Star LevelCriteria
4*World-leading journals. Paper must have: exceptional novelty (score 85+), rigorous identification, clean causal story, broad implications, polished writing. Very selective — only recommend if the paper is truly outstanding.
4Top field journals. Paper should have: high novelty (score 70+), solid identification strategy, clear contribution, well-executed empirics.
3Highly regarded journals. Paper should have: moderate-to-high novelty (score 55+), reasonable identification, clear results, good execution.
2Well-recognized journals. Paper with: some novelty (score 40+), standard methodology, sound results.
1Recognized journals. Paper with: limited novelty, basic methodology, narrow contribution.

Decision rules:

  • Novelty score alone does not determine the star level — also consider methodology rigor, data quality, writing quality, and scope of implications.
  • If the paper uses a novel identification strategy (natural experiment, RDD, etc.), upgrade by 0.5 star.
  • If the paper uses Chinese data targeting international journals, be realistic: Chinese-market papers rarely appear in 4* journals unless the finding has universal implications.
  • Be honest and calibrated. Over-optimistic recommendations waste the author's time.

Present the assessment:

领域匹配与星级评估:

最佳匹配领域:
  1. [Field 1] — [rationale]
  2. [Field 2] — [rationale]

建议投稿星级:ABS [N] 星
理由:
- 创新性:[novelty score] 分,[assessment]
- 方法论:[methodology assessment]
- 数据质量:[data assessment]
- 贡献范围:[scope assessment]

是否同意以上评估?如需调整星级,请告知。

Wait for user confirmation before proceeding.


Phase 4: Journal Recommendations

Step 4a: Extract Journal Data from ABS PDF

Read the ABS journal list PDF (C:\Users\Admin\.claude\skills\paper-submission\asset\Business School Journal List 2023.pdf) using a Python script to extract all journals matching:

  • Field = one of the 2 identified fields
  • ABS star rating = the recommended level (also include one level above and one level below for reference)
  • SSCI indexed = Yes (prioritize SSCI journals, but include non-SSCI journals as backup)

Use the following Python approach via Bash:

import fitz
doc = fitz.open(r'C:\Users\Admin\.claude\skills\paper-submission\asset\Business School Journal List 2023.pdf')
# Parse the tabular data from each page
# Extract: ISSN, Field, Journal Title, ABS rating, ABDC rating, SSCI status, JCR quartile, JIF
Step 4b: Rank and Select 20 Journals

From the extracted journals, select the top 20 recommendations across the 2 fields. Ranking criteria:

  1. Field relevance: How well the journal's scope matches the paper's topic
  2. Star level match: Journals at the recommended star level ranked first
  3. SSCI status: SSCI-indexed journals preferred
  4. JIF: Higher impact factor preferred (as tiebreaker)
  5. Publication precedent: Journals that have published similar topics (based on your knowledge)

Organize the list as:

  • Field 1: 10 journals (ranked by fit)
  • Field 2: 10 journals (ranked by fit)

For each journal, provide:

  • Journal name
  • ABS star rating
  • SSCI status and JCR quartile
  • JIF (if available)
  • 1-sentence rationale for why this journal fits the paper

Phase 5: Report Generation

Generate the final report as target.pdf saved in the paper's directory (or user-specified location).

Report Structure

The report should contain:

═══════════════════════════════════════════
        论文投稿目标评估报告
        Paper Submission Target Report
═══════════════════════════════════════════

生成日期:[YYYY-MM-DD]
论文标题:[Paper title if available]

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

一、论文概要
[200-word paper summary]

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

二、文献创新性评估

综合得分:[SCORE]/100 — [Rating]

[For each dimension:]
维度 [N]: [Name] — [Sub-score]/100
  相关文献:[2-3 papers]
  本文创新:[How this paper differs]

主要创新点:
1. [...]
2. [...]
3. [...]

潜在审稿风险:
- [...]

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

三、目标领域与星级

最佳领域:[Field 1], [Field 2]
建议星级:ABS [N] 星

评估维度:
- 创新性:[...]
- 方法论:[...]
- 数据质量:[...]
- 贡献范围:[...]

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

四、推荐期刊(共20本)

[Field 1 Name](10本):
┌────┬──────────────────────┬──────┬──────┬──────┬─────────────────────────┐
│ #  │ Journal              │ ABS  │ SSCI │ JIF  │ 推荐理由                │
├────┼──────────────────────┼──────┼──────┼──────┼─────────────────────────┤
│ 1  │ ...                  │ ...  │ ...  │ ...  │ ...                     │
│ ...│                      │      │      │      │                         │
└────┴──────────────────────┴──────┴──────┴──────┴─────────────────────────┘

[Field 2 Name](10本):
┌────┬──────────────────────┬──────┬──────┬──────┬─────────────────────────┐
│ #  │ Journal              │ ABS  │ SSCI │ JIF  │ 推荐理由                │
├────┼──────────────────────┼──────┼──────┼──────┼─────────────────────────┤
│ 1  │ ...                  │ ...  │ ...  │ ...  │ ...                     │
│ ...│                      │      │      │      │                         │
└────┴──────────────────────┴──────┴──────┴──────┴─────────────────────────┘

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

五、投稿建议

[2-3 paragraphs of strategic advice:]
- Which journal to try first and why
- Backup strategy if rejected
- Any adjustments to the paper that would improve chances at higher-tier journals
PDF Generation Method

Use the Python script scripts/generate_report.py to produce the PDF. The script uses fpdf2 with Chinese font support (SimSun from C:\Windows\Fonts\simsun.ttc).

Interaction pattern:

报告已生成并保存至:[path]/target.pdf

报告包含:
- 创新性评估:[SCORE]/100
- 推荐领域:[Field 1], [Field 2]
- 推荐星级:ABS [N] 星
- 推荐期刊:20本(每个领域10本)

Important Notes

  • Web search is mandatory for Phase 2. Do not skip novelty assessment.
  • Be calibrated and honest in scoring. An inflated score wastes the author's time on unrealistic targets.
  • ABS journal list PDF is the authoritative source for journal data. Extract data programmatically from the PDF — do not rely on memory alone.
  • SSCI indexing is strongly preferred but not strictly required. If fewer than 10 SSCI journals exist in a field at the target star level, supplement with non-SSCI journals and mark them clearly.
  • Star level flexibility: The 20 journal recommendations should primarily be at the recommended star level. If fewer than 10 journals exist at that level in a field, include journals from one level above or below, clearly marked.
  • The report language is Chinese for headings and explanations, English for journal names and academic content.
  • If the user provides a specific target journal or field preference, adjust recommendations accordingly.
  • The output file is always named target.pdf unless the user specifies otherwise.

Signals

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Source
github.com/brycewang-stanford/auto-empirical-research-skills