Zafer-Liu

Zafer-Liu / info-research-report

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信息调研报告自动化 - Automated Information Research Report Skill for OpenClaw

39
0
69% credibility
Found Apr 07, 2026 at 39 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

This tool automates creating professional DOCX research reports from web search results by summarizing content with AI and emailing the output.

How It Works

1
📰 Discover the report maker

You find a simple tool that turns your web searches into professional research reports, saving hours of writing.

2
🔍 Search your topic

You quickly search online for articles and info about your research subject using a basic search page.

3
📋 Collect top findings

You grab the best links, titles, and snippets, saving them in a simple list file.

4
✨ Generate the report

You share your topic, email address, and list with the tool – it gathers details, smartly summarizes with AI help, and crafts a polished document.

5
⚙️ Choose detail level

Pick quick mode for speed or full mode to dive deeper into page contents.

📧 Report delivered

A beautiful, official-style report with summaries, trends, risks, and sources arrives safely in your inbox, ready to share.

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Star Growth

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AI-Generated Review

What is info-research-report?

This Python tool automates generating formal Chinese DOCX research reports on any topic, pulling DuckDuckGo search results, fetching web content via browser integration, and using LLMs like MiniMax or OpenAI for structured summaries on background, trends, and risks. Run it via CLI like `python run.py "US Iran War" "user@example.com" results.json --no-fetch` to skip fetching for speed, and it emails the polished output with sections like findings, sources, and references. It solves the drudgery of manual info research and report assembly for quick, agency-style deliverables.

Why is it gaining traction?

It stands out with end-to-end automation—search to LLM-powered extraction, categorization (policy/industry/tech), and email delivery—without needing custom scripts, akin to automated GitHub releases but for information processing and retrieval. Developers dig the seamless OpenClaw browser/email hooks and optional API keys for flexible LLM backends, delivering pro reports in minutes versus hours of copy-pasting. The structured prompts ensure consistent, objective output, beating basic scrapers or manual LLM chats.

Who should use this?

Policy analysts or security researchers needing rapid Chinese reports from web data, especially in OpenClaw workflows. Info teams handling event datasets for automated information mapping and extraction with LLMs, or devs automating research pipelines like GitHub automated documentation for equity reports.

Verdict

Grab it for niche automated information systems if you're in the ecosystem—39 stars show early interest, solid README, but 0.7% credibility flags immaturity with no tests or broad adoption. Prototype-worthy for custom tweaks, skip for production without hardening.

(198 words)

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