| name | paper-submission |
| description | 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" / "ๆ็จฟ่ฏไผฐ" / "ๆๅๆจ่" / "target journal" / "้ๅ". |
| allowed-tools | Read, Bash, Edit, Write, Glob, Grep, AskUserQuestion, WebSearch, WebFetch, Agent |
| argument-hint | [path-to-paper-pdf-or-project-folder] |
Paper Submission Evaluator
Overview
This skill evaluates an academic paper and produces a comprehensive submission target report. It performs four assessments:
- Contribution Novelty Score (0-100): How much the paper advances existing literature, assessed via web search for related work.
- Best-Fit SSCI Journal Fields: Which ABS field categories best match the paper.
- Appropriate ABS Star Rating: What star level (1, 2, 3, 4, 4*) the paper's quality warrants.
- 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
- 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.)
- 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.
- 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)
- Summarize the paper in ~200 words for use in subsequent phases. Present this summary to the user for confirmation:
ๆๅทฒ้
่ฏป่ฎบๆ๏ผไปฅไธๆฏๆ่ฆ๏ผ
็ ็ฉถ้ฎ้ข๏ผ[...]
ๆนๆณ๏ผ[...]
ๆฐๆฎ๏ผ[...]
ไธป่ฆๅ็ฐ๏ผ[...]
่ดก็ฎๆนๅ๏ผ[...]
่ฏท็กฎ่ฎคไปฅไธ็่งฃๆฏๅฆๆญฃ็กฎ๏ผๆ่ฟ่ก่ฐๆดใ
- 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:
- Execute the WebSearch query.
- Read the top results using WebFetch to check abstracts and findings.
- 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 Range | Meaning | Criteria |
|---|
| 85-100 | Highly novel | No prior paper addresses this exact question with this approach. Opens a new research direction. |
| 70-84 | Substantially novel | Few prior papers on a similar topic, but this paper offers a clearly distinct angle (new data, new mechanism, new identification). |
| 55-69 | Moderately novel | Topic has been studied, but this paper contributes incremental insights (new setting, additional robustness, extension of known results). |
| 40-54 | Limited novelty | Multiple papers have addressed similar questions with similar methods. Contribution is primarily confirmatory or extends to a new sample. |
| 0-39 | Low novelty | The 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:
ๆ็ฎๅๆฐๆง่ฏไผฐ็ปๆ๏ผ
็ปดๅบฆ1: [dimension name] โ ๅญๅ [X]/100
ๅทฒๆๆ็ฎ๏ผ[list 2-3 most relevant prior papers with year]
ๆฌๆๅบๅซ๏ผ[how this paper differs]
็ปดๅบฆ2: [dimension name] โ ๅญๅ [X]/100
...
็ปผๅๅๆฐๆงๅพๅ๏ผ[SCORE]/100
่ฏ็บง๏ผ[Highly novel / Substantially novel / Moderately novel / Limited novelty / Low novelty]
ไธป่ฆๅๆฐ็น๏ผ
1. [innovation point 1]
2. [innovation point 2]
3. [innovation point 3]
ๆฝๅจ้ฃ้ฉ๏ผ
- [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 โ FINANCE)
- What is a strong secondary field? (e.g., uses accounting data โ ACCOUNT; studies innovation โ 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 Level | Criteria |
|---|
| 4* | World-leading journals. Paper must have: exceptional novelty (score 85+), rigorous identification, clean causal story, broad implications, polished writing. Very selective โ only recommend if the paper is truly outstanding. |
| 4 | Top field journals. Paper should have: high novelty (score 70+), solid identification strategy, clear contribution, well-executed empirics. |
| 3 | Highly regarded journals. Paper should have: moderate-to-high novelty (score 55+), reasonable identification, clear results, good execution. |
| 2 | Well-recognized journals. Paper with: some novelty (score 40+), standard methodology, sound results. |
| 1 | Recognized journals. Paper with: limited novelty, basic methodology, narrow contribution. |
Decision rules:
- Novelty score alone does not determine the star level โ 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:
้ขๅๅน้
ไธๆ็บง่ฏไผฐ๏ผ
ๆไฝณๅน้
้ขๅ๏ผ
1. [Field 1] โ [rationale]
2. [Field 2] โ [rationale]
ๅปบ่ฎฎๆ็จฟๆ็บง๏ผABS [N] ๆ
็็ฑ๏ผ
- ๅๆฐๆง๏ผ[novelty score] ๅ๏ผ[assessment]
- ๆนๆณ่ฎบ๏ผ[methodology assessment]
- ๆฐๆฎ่ดจ้๏ผ[data assessment]
- ่ดก็ฎ่ๅด๏ผ[scope assessment]
ๆฏๅฆๅๆไปฅไธ่ฏไผฐ๏ผๅฆ้่ฐๆดๆ็บง๏ผ่ฏทๅ็ฅใ
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')
Step 4b: Rank and Select 20 Journals
From the extracted journals, select the top 20 recommendations across the 2 fields. Ranking criteria:
- Field relevance: How well the journal's scope matches the paper's topic
- Star level match: Journals at the recommended star level ranked first
- SSCI status: SSCI-indexed journals preferred
- JIF: Higher impact factor preferred (as tiebreaker)
- 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:
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
่ฎบๆๆ็จฟ็ฎๆ ่ฏไผฐๆฅๅ
Paper Submission Target Report
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
็ๆๆฅๆ๏ผ[YYYY-MM-DD]
่ฎบๆๆ ้ข๏ผ[Paper title if available]
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
ไธใ่ฎบๆๆฆ่ฆ
[200-word paper summary]
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
ไบใๆ็ฎๅๆฐๆง่ฏไผฐ
็ปผๅๅพๅ๏ผ[SCORE]/100 โ [Rating]
[For each dimension:]
็ปดๅบฆ [N]: [Name] โ [Sub-score]/100
็ธๅ
ณๆ็ฎ๏ผ[2-3 papers]
ๆฌๆๅๆฐ๏ผ[How this paper differs]
ไธป่ฆๅๆฐ็น๏ผ
1. [...]
2. [...]
3. [...]
ๆฝๅจๅฎก็จฟ้ฃ้ฉ๏ผ
- [...]
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
ไธใ็ฎๆ ้ขๅไธๆ็บง
ๆไฝณ้ขๅ๏ผ[Field 1], [Field 2]
ๅปบ่ฎฎๆ็บง๏ผABS [N] ๆ
่ฏไผฐ็ปดๅบฆ๏ผ
- ๅๆฐๆง๏ผ[...]
- ๆนๆณ่ฎบ๏ผ[...]
- ๆฐๆฎ่ดจ้๏ผ[...]
- ่ดก็ฎ่ๅด๏ผ[...]
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
ๅใๆจ่ๆๅ๏ผๅ
ฑ20ๆฌ๏ผ
[Field 1 Name]๏ผ10ๆฌ๏ผ:
โโโโโโฌโโโโโโโโโโโโโโโโโโโโโโโฌโโโโโโโฌโโโโโโโฌโโโโโโโฌโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ # โ Journal โ ABS โ SSCI โ JIF โ ๆจ่็็ฑ โ
โโโโโโผโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโผโโโโโโโผโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ 1 โ ... โ ... โ ... โ ... โ ... โ
โ ...โ โ โ โ โ โ
โโโโโโดโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโดโโโโโโโดโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโ
[Field 2 Name]๏ผ10ๆฌ๏ผ:
โโโโโโฌโโโโโโโโโโโโโโโโโโโโโโโฌโโโโโโโฌโโโโโโโฌโโโโโโโฌโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ # โ Journal โ ABS โ SSCI โ JIF โ ๆจ่็็ฑ โ
โโโโโโผโโโโโโโโโโโโโโโโโโโโโโโผโโโโโโโผโโโโโโโผโโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโค
โ 1 โ ... โ ... โ ... โ ... โ ... โ
โ ...โ โ โ โ โ โ
โโโโโโดโโโโโโโโโโโโโโโโโโโโโโโดโโโโโโโดโโโโโโโดโโโโโโโดโโโโโโโโโโโโโโโโโโโโโโโโโโ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
ไบใๆ็จฟๅปบ่ฎฎ
[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:
ๆฅๅๅทฒ็ๆๅนถไฟๅญ่ณ๏ผ[path]/target.pdf
ๆฅๅๅ
ๅซ๏ผ
- ๅๆฐๆง่ฏไผฐ๏ผ[SCORE]/100
- ๆจ่้ขๅ๏ผ[Field 1], [Field 2]
- ๆจ่ๆ็บง๏ผABS [N] ๆ
- ๆจ่ๆๅ๏ผ20ๆฌ๏ผๆฏไธช้ขๅ10ๆฌ๏ผ
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 โ 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.