RRepoGEO

REPOGEO REPORT · LITE

langchain-ai/local-deep-researcher

Default branch main · commit e1721099 · scanned 5/11/2026, 9:48:39 PM

GitHub: 9,138 stars · 954 forks

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 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/local-deep-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 README opening to clarify unique value proposition

    Why:

    CURRENT
    Local Deep Researcher is a fully local web research assistant that uses any LLM hosted by Ollama or LMStudio. Give it a topic and it will generate a web search query, gather web search results, summarize the results of web search, reflect on the summary to examine knowledge gaps, generate a new search query to address the gaps, and repeat for a user-defined number of cycles. It will provide the user a final markdown summary with all sources used to generate the summary.
    COPY-PASTE FIX
    Local Deep Researcher is a fully local web research and report writing assistant designed for complete privacy and autonomy, leveraging any LLM hosted by Ollama or LMStudio. Unlike general LLM frameworks or cloud-dependent agents, it provides an end-to-end, multi-cycle research workflow entirely on your machine: generating queries, gathering results, summarizing, reflecting on knowledge gaps, and producing a final markdown report with all sources.
  • mediumcomparison#2
    Add a comparison section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, perhaps titled 'Why Local Deep Researcher?' or 'Comparison with Alternatives', that explicitly contrasts its fully local, autonomous research capabilities and privacy benefits with general LLM frameworks (like LangChain or LlamaIndex) and cloud-based research agents.

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/local-deep-researcher
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
run-llama/llama_index
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. run-llama/llama_index · recommended 2×
  2. langchain-ai/langchain · recommended 2×
  3. deepset-ai/haystack · recommended 2×
  4. Llama 3 · recommended 1×
  5. ollama/ollama · recommended 1×
  • CATEGORY QUERY
    How to build an AI assistant for comprehensive web research and report generation locally?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex (run-llama/llama_index)
    2. Llama 3
    3. Ollama (ollama/ollama)
    4. Playwright (microsoft/playwright)
    5. Selenium (SeleniumHQ/selenium)
    6. LangChain (langchain-ai/langchain)
    7. Beautiful Soup (crummy/BeautifulSoup4)
    8. Scrapy (scrapy/scrapy)
    9. NLTK (nltk/nltk)
    10. spaCy (explosion/spaCy)
    11. Haystack (deepset-ai/haystack)
    12. Puppeteer (puppeteer/puppeteer)

    AI recommended 12 alternatives but never named langchain-ai/local-deep-researcher. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools can help an LLM autonomously research topics, summarize findings, and identify knowledge gaps?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. AutoGPT / BabyAGI (Significant-Gravitas/AutoGPT)
    4. Haystack (deepset-ai/haystack)
    5. You.com
    6. Perplexity AI

    AI recommended 6 alternatives but never named langchain-ai/local-deep-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
    warn

    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/local-deep-researcher?
    pass
    AI did not name langchain-ai/local-deep-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/local-deep-researcher in production, what risks or prerequisites should they evaluate first?
    pass
    AI named langchain-ai/local-deep-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/local-deep-researcher solve, and who is the primary audience?
    pass
    AI named langchain-ai/local-deep-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/local-deep-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