RRepoGEO

REPOGEO REPORT · LITE

langchain-ai/multi-modal-researcher

Default branch main · commit f0538d3e · scanned 6/7/2026, 3:52:35 AM

GitHub: 591 stars · 99 forks

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
2 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface langchain-ai/multi-modal-researcher, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's opening paragraph to highlight multi-modal agent capabilities

    Why:

    CURRENT
    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.
    COPY-PASTE FIX
    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#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    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.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface langchain-ai/multi-modal-researcher
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ChatGPT
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ChatGPT · recommended 2×
  2. Otter.ai · recommended 2×
  3. Zapier · recommended 1×
  4. Make · recommended 1×
  5. Integrately · recommended 1×
  • CATEGORY QUERY
    How to automate research and content generation from web and video sources?
    you: not recommended
    AI recommended (in order):
    1. Zapier
    2. Make
    3. Integrately
    4. ChatGPT
    5. Claude
    6. Google Gemini
    7. YouTube Data API v3
    8. Google Cloud Video Intelligence API
    9. Beautiful Soup (crummy/BeautifulSoup)
    10. Puppeteer (puppeteer/puppeteer)
    11. Scrapy (scrapy/scrapy)
    12. Otter.ai
    13. Descript
    14. Happy Scribe
    15. Feedly
    16. Airtable
    17. Notion
    18. Google Sheets

    AI recommended 18 alternatives but never named langchain-ai/multi-modal-researcher. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tool to summarize YouTube videos and web articles into a research report and podcast?
    you: not recommended
    AI recommended (in order):
    1. ChatGPT
    2. Claude 3
    3. Notion AI
    4. Eightify
    5. Bearly.ai
    6. Summarize.tech
    7. TLDR This
    8. Otter.ai

    AI recommended 8 alternatives but never named langchain-ai/multi-modal-researcher. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of langchain-ai/multi-modal-researcher?
    pass
    AI did not name langchain-ai/multi-modal-researcher — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts langchain-ai/multi-modal-researcher in production, what risks or prerequisites should they evaluate first?
    pass
    AI named langchain-ai/multi-modal-researcher explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo langchain-ai/multi-modal-researcher solve, and who is the primary audience?
    pass
    AI named langchain-ai/multi-modal-researcher explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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langchain-ai/multi-modal-researcher — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite
langchain-ai/multi-modal-researcher — RepoGEO report