RRepoGEO

REPOGEO REPORT · LITE

lcdevelop/ChatBotCourse

Default branch master · commit 8194902f · scanned 5/26/2026, 11:58:29 PM

GitHub: 6,017 stars · 1,653 forks

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 lcdevelop/ChatBotCourse, 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.

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 lcdevelop/ChatBotCourse
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Dialogflow
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Dialogflow · recommended 1×
  2. RasaHQ/rasa · recommended 1×
  3. huggingface/transformers · recommended 1×
  4. nltk/nltk · recommended 1×
  5. explosion/spaCy · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive tutorial to build a chatbot using natural language processing?
    you: not recommended
    AI recommended (in order):
    1. Dialogflow
    2. Rasa (RasaHQ/rasa)
    3. Hugging Face Transformers Library (huggingface/transformers)
    4. NLTK (Natural Language Toolkit) (nltk/nltk)
    5. SpaCy (explosion/spaCy)
    6. PyTorch (pytorch/pytorch)
    7. TensorFlow (tensorflow/tensorflow)

    AI recommended 7 alternatives but never named lcdevelop/ChatBotCourse. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How do I implement core natural language processing techniques for a custom conversational AI?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. spaCy
    3. NLTK (Natural Language Toolkit)
    4. Rasa
    5. Gensim
    6. FastText

    AI recommended 6 alternatives but never named lcdevelop/ChatBotCourse. 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 lcdevelop/ChatBotCourse?
    pass
    AI named lcdevelop/ChatBotCourse explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of lcdevelop/ChatBotCourse. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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lcdevelop/ChatBotCourse — 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