skills/67-econfin-workflow-toolkit/paper-submission/SKILL.md
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".
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research paper-submissionInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
This skill evaluates an academic paper and produces a comprehensive submission target report. It performs four assessments:
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.
$ARGUMENTS or ask). Accept either:
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。
This phase evaluates how novel the paper's contribution is relative to existing literature. Web search is mandatory.
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:
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-analysisFor each search:
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:
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]"]
The ABS journal list uses these field categories (22 fields total):
Based on the paper's topic, methodology, and data, identify the 2 most suitable fields. Consider:
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 — 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:
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.
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:
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
From the extracted journals, select the top 20 recommendations across the 2 fields. Ranking criteria:
Organize the list as:
For each journal, provide:
Generate the final report as target.pdf saved in the paper's directory (or user-specified location).
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
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)
target.pdf unless the user specifies otherwise.tools
Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool should I use to..." OR "install/run/use <tool> to ..." for research/lit-review work: automating a survey or related-work section, PDF→Markdown extraction for LLMs (MinerU/marker/docling), PRISMA / systematic review (ASReview), citation-backed Q&A over PDFs (PaperQA2), wiring papers into Claude/Cursor via MCP (arxiv/paper-search/zotero servers), or chatting with a Zotero library. Ships a launcher (scripts/litrun.py) that installs each tool in an isolated venv and runs it. Curated catalog of 70+ vetted projects. 支持中英文(用于「文献综述工具选型」与「一键安装/运行」)。
development
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows without reading the entire repository at once.
documentation
Use when the project collects primary data or runs a field, lab, or survey experiment, before the intervention begins — write the pre-analysis plan, size the sample from a power calculation, and register with the AEA RCT Registry. Apply after the design is chosen in aer-identification and before any outcome data are seen.
tools
Guide economists to authoritative data sources with explicit, confirmed data specifications before retrieval; interfaces with Playwright MCP to navigate portals and extract real data, not articles about data.