chtc66

chtc66 / academic-skills

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Academic workflow skills for paper reading, survey writing, experiment summarization, rebuttal drafting, and weekly lab updates.

17
1
100% credibility
Found Apr 06, 2026 at 17 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

A set of ready-to-use AI assistants and scripts that help researchers summarize papers, extract benchmarks, write surveys, and generate digests from arXiv, primarily in Chinese.

How It Works

1
🔍 Discover Research Helpers

You stumble upon a handy collection of smart assistants designed to simplify tough academic tasks like reading papers and summarizing experiments.

2
📋 Choose Your Assistant

Pick the perfect helper for what you need, such as deep notes on a paper, finding research gaps, or creating weekly lab updates.

3
🔗 Link the Smart Thinker

Connect the assistant to an AI service so it can read and analyze your research materials just like a brilliant colleague.

4
📄 Share Your Work

Give it a paper, experiment log, arXiv keywords, or reviewer comments to process into useful insights.

5
✨ Receive Clear Outputs

Get beautifully organized Chinese notes, tables, summaries, digests, or rebuttals that highlight key points without fluff.

6
📤 Use or Share Results

Save the structured insights for yourself, send a digest to your team chat, or build on them for your next paper.

🎉 Research Supercharged

You now breeze through literature reviews and updates, freeing up time for groundbreaking ideas and real progress.

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AI-Generated Review

What is academic-skills?

This Python project delivers AI agents powered by OpenAI prompts to streamline academic workflows, like generating deep-reading notes from papers, drafting literature surveys, summarizing experiment logs, extracting benchmarks, finding research gaps, writing review rebuttals, and creating weekly lab updates—all often in Chinese. It includes a CLI tool to fetch recent arXiv papers by category and keywords, rank them for relevance, infer contributions and limitations from abstracts, and post Markdown digests directly to Feishu via webhook. Think academic GitHub Copilot meets workflow AI: plug in papers or logs, get structured outputs ready for notes or reports.

Why is it gaining traction?

Pre-tuned prompts keep outputs grounded—no hallucinated claims—and handle Chinese naturally, standing out from generic chatbots for precise academic tasks like conservative arXiv ranking or rebuttal drafting. The Feishu integration and CLI for daily paper digests hook busy researchers needing quick, shareable summaries without manual scraping. It's a lightweight academic skills hub, exportable as zipped agent configs for platforms like CrewAI.

Who should use this?

PhD students or postdocs in AI/ML grinding through paper reading and surveys; lab leads drafting weekly updates from experiment logs; reviewers prepping rebuttals without overclaiming evidence. Ideal for teams using Feishu for arXiv alerts in cs.AI or cs.CL.

Verdict

With 17 stars and 1.0% credibility score, it's raw and early—docs are sparse, no tests visible—but the arXiv digest script alone justifies a test run for daily workflows. Fork and tweak prompts if academic workflow AI fits your stack; skip if you need battle-tested polish.

(198 words)

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