REPOGEO 报告 · LITE
langchain-ai/multi-modal-researcher
默认分支 main · commit f0538d3e · 扫描时间 2026/6/7 03:52:35
星标 591 · Fork 99
行动计划告诉你下一步要做什么——按影响力排序、可直接复制粘贴的修改。品类可见性是真正的 GEO 测试:当用户向 AI 提一个不带品牌、本应让 langchain-ai/multi-modal-researcher 浮出水面的问题时,AI 是真的推荐了你,还是推荐了你的竞品?客观检查验证 AI 引擎最先权衡的那些元数据信号。自指检查判断 AI 是否还认识你的名字。
行动计划 — 可复制粘贴的修复
2 条由 gemini-2.5-flash 生成、按优先级排序的修改。修完后请把对应条目标记为完成。
- highreadme#1Reposition the README's opening paragraph to highlight multi-modal agent capabilities
原因:
当前This project is a simple research and podcast generation workflow that uses LangGraph with the unique capabilities of Google's Gemini 2.5 model family. It combines three useful features of the Gemini 2.5 model family. You can pass a research topic and, optionally, a YouTube video URL. The system will then perform research on the topic using search, analyze the video, combine the insights, and generate a report with citations as well as a short podcast on the topic for you.
复制粘贴的修复Multi-Modal Researcher is an autonomous AI agent built with LangGraph and Google Gemini 2.5, designed to automate comprehensive research and content generation from diverse sources including web and YouTube videos. It synthesizes insights into detailed reports and podcasts, leveraging Gemini's native video understanding, Google Search, and multi-speaker text-to-speech capabilities.
- highlicense#2Add a LICENSE file to the repository
原因:
复制粘贴的修复Add a LICENSE file (e.g., MIT, Apache-2.0, or GPL-3.0) to the repository root, clearly stating the project's terms of use.
本次扫描解析到的品类 GEO 通道:google/gemini-2.5-flash, deepseek/deepseek-v4-flash
品类可见性 — 真正的 GEO 测试
向 google/gemini-2.5-flash 提出的不带品牌问题。AI 推荐了你,还是推荐了别人?
各模型使用同一组问题 — 切换标签对比回答与排名。
- ChatGPT · 被推荐 2 次
- Otter.ai · 被推荐 2 次
- Zapier · 被推荐 1 次
- Make · 被推荐 1 次
- Integrately · 被推荐 1 次
- 品类问题How to automate research and content generation from web and video sources?你:未被推荐AI 推荐顺序:
- Zapier
- Make
- Integrately
- ChatGPT
- Claude
- Google Gemini
- YouTube Data API v3
- Google Cloud Video Intelligence API
- Beautiful Soup (crummy/BeautifulSoup)
- Puppeteer (puppeteer/puppeteer)
- Scrapy (scrapy/scrapy)
- Otter.ai
- Descript
- Happy Scribe
- Feedly
- Airtable
- Notion
- Google Sheets
AI 推荐了 18 个替代方案,却始终没点名 langchain-ai/multi-modal-researcher。这就是要补上的差距。
查看 AI 完整回答
- 品类问题Tool to summarize YouTube videos and web articles into a research report and podcast?你:未被推荐AI 推荐顺序:
- ChatGPT
- Claude 3
- Notion AI
- Eightify
- Bearly.ai
- Summarize.tech
- TLDR This
- Otter.ai
AI 推荐了 8 个替代方案,却始终没点名 langchain-ai/multi-modal-researcher。这就是要补上的差距。
查看 AI 完整回答
客观检查
针对 AI 引擎最看重的元数据信号的规则审计。
- Metadata completenessfail
建议:
- README presencepass
自指检查
当被直接问到你时,AI 是否还知道你的仓库存在?
- Compared to common alternatives in this category, what is the core differentiator of langchain-ai/multi-modal-researcher?passAI 未点名 langchain-ai/multi-modal-researcher —— 很可能在说另一个项目
AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?
- If a team adopts langchain-ai/multi-modal-researcher in production, what risks or prerequisites should they evaluate first?passAI 明确点名了 langchain-ai/multi-modal-researcher
AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?
- In one sentence, what problem does the repo langchain-ai/multi-modal-researcher solve, and who is the primary audience?passAI 明确点名了 langchain-ai/multi-modal-researcher
AI 的回答可能信誓旦旦却是错的。请按事实核对:技术栈、目标人群、差异化点是不是和你实际的对得上?
嵌入你的 GEO 徽章
把这个徽章贴进 langchain-ai/multi-modal-researcher 的 README。每次重新扫描都会自动更新,并跳到最新报告——是「我在乎 AI 可发现性」最简单的公开证明。
[](https://repogeo.com/zh/r/langchain-ai/multi-modal-researcher)<a href="https://repogeo.com/zh/r/langchain-ai/multi-modal-researcher"><img src="https://repogeo.com/badge/langchain-ai/multi-modal-researcher.svg" alt="RepoGEO" /></a>订阅 Pro,解锁深度诊断
langchain-ai/multi-modal-researcher — 轻量扫描仍免费;本卡列出 Pro 相对轻量的深度额度。
- 深度报告每月 10 次
- 无品牌品类查询5,轻量 2
- 优先行动项8,轻量 3