WantongC

WantongC / journal-adapt-writing-skill

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Learn any journal's writing conventions from its published papers, then revise your manuscript to match — section by section.

academic-writing claude economics journal latex
27
1
100% credibility
Found May 13, 2026 at 27 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
AI Summary

This repository provides a skill for AI writing assistants that studies sample papers from a target academic journal to generate custom style rules and then revises user manuscripts accordingly.

How It Works

1
đź’ˇ Discover the helper

You find a smart writing assistant that learns any journal's unique style from its own published papers to help polish your work.

2
đź“š Gather journal papers

You collect a small folder of 5 to 8 recent papers from your target journal so the assistant can study real examples.

3
🔍 Study the journal's style

You tell the assistant to read those papers and create a custom set of writing rules just for that journal.

4
âś… Review and approve rules

You look over the suggested rules, make sure they feel right, and give your okay to use them.

5
đź“„ Share your paper

You hand over your manuscript and choose which sections—like intro or abstract—you want revised.

6
✨ Get style-matched revisions

The assistant carefully rewrites your sections to match the journal's voice, keeping all your facts and numbers safe.

🎉 Ready for submission

You receive neat revised files with clear notes on every change, making your paper journal-perfect and submission-ready.

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AI-Generated Review

What is journal-adapt-writing-skill?

This Claude Code skill helps academics adapt manuscripts to any journal's unwritten style rules by analyzing 5-8 sample papers. Drop in a folder of journal PDFs (via MinerU conversion), pick your discipline, and upload your draft—it spits out revised Markdown sections with detailed logs explaining every change. No more guessing if your intro matches Management Science's puzzle format or IJPE's prose preferences; it's like learn anything ai tailored for journal-specific writing conventions.

Why is it gaining traction?

Unlike static writing tools with one-size-fits-all advice, it builds custom rulesets from your target journal's corpus, prioritizing strong signals (patterns in 3+ papers) over generic norms. The phased workflow—you approve rules before revisions—plus per-section logs and preservation of equations/citations, gives users control without full automation. Invoke with /journal-adapt or natural prompts like "revise for NeurIPS," and it handles full papers or sections.

Who should use this?

PhD students and postdocs in economics, ML/CV/NLP, or CS/engineering prepping submissions to venue-specific journals. Researchers reusing papers across conferences like ICML or ACM. Anyone with English Markdown/PDF drafts frustrated by reviewer nitpicks on structure and rhetoric.

Verdict

Solid docs, examples, and MIT license make it approachable, but 27 stars and 1.0% credibility score reflect early-stage maturity—expect MinerU quirks like table issues. Try it for low-stakes revisions in supported fields; contribute base rules to extend it.

(198 words)

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