RRepoGEO

REPOGEO REPORT · LITE

BinNong/meet-libai

Default branch main · commit e5b8bd78 · scanned 6/25/2026, 7:37:47 PM

GitHub: 1,885 stars · 232 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
35 /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
3 / 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 BinNong/meet-libai, 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

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

OVERALL DIRECTION
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ["AI agent", "knowledge graph", "large language model", "Chinese poetry", "Li Bai", "cultural heritage", "generative AI", "chatbot", "RAG"]
  • highreadme#2
    Add a concise project summary after the main title

    Why:

    CURRENT
    (The current README starts with H1, then badges, then "1. 项目背景")
    COPY-PASTE FIX
    (After the H1 "# 「遇见李白」 meet-libai" and before "1. 项目背景")

本项目旨在通过构建李白知识图谱，结合大模型训练出专业的AI智能体，以生成式对话应用的形式，推动李白文化的普及与推广。
  • mediumhomepage#3
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    (Add a URL to a live demo, project website, or detailed documentation page here, e.g., "https://meet-libai.example.com")

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 BinNong/meet-libai
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Amazon Neptune
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Amazon Neptune · recommended 2×
  2. Neo4j · recommended 1×
  3. Grakn (now Vaticle's TypeDB) · recommended 1×
  4. Wikidata · recommended 1×
  5. DBpedia · recommended 1×
  • CATEGORY QUERY
    How to build an AI chatbot for historical figures using knowledge graphs?
    you: not recommended
    AI recommended (in order):
    1. Neo4j
    2. Amazon Neptune
    3. Grakn (now Vaticle's TypeDB)
    4. Wikidata
    5. DBpedia
    6. OpenRefine
    7. Pandas
    8. RDFLib
    9. Neo4j Driver
    10. Rasa
    11. Google Dialogflow
    12. OpenAI GPT-3.5/GPT-4
    13. neo4j-driver
    14. gremlinpython
    15. sparqlwrapper
    16. LangChain

    AI recommended 16 alternatives but never named BinNong/meet-libai. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking tools to integrate knowledge graphs with large language models for domain-specific Q&A.
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. Neo4j (neo4j/neo4j)
    4. TypeDB (vaticle/typedb)
    5. RDFox
    6. Stardog
    7. Amazon Neptune

    AI recommended 7 alternatives but never named BinNong/meet-libai. 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 BinNong/meet-libai?
    pass
    AI named BinNong/meet-libai explicitly

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

  • If a team adopts BinNong/meet-libai in production, what risks or prerequisites should they evaluate first?
    pass
    AI named BinNong/meet-libai 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 BinNong/meet-libai solve, and who is the primary audience?
    pass
    AI named BinNong/meet-libai explicitly

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

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BinNong/meet-libai — 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