RRepoGEO

REPOGEO REPORT · LITE

CSML-by-Clevy/csml-engine

Default branch dev · commit d0f80bbc · scanned 6/16/2026, 11:27:23 AM

GitHub: 721 stars · 63 forks

AI VISIBILITY SCORE
33 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 CSML-by-Clevy/csml-engine, 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
  • highreadme#1
    Add a descriptive H1 title to the README

    Why:

    CURRENT
    <h1 align="center">
  <br>
  <a href="https://www.csml.dev"></a>
  <br>

</h1>
    COPY-PASTE FIX
    <h1 align="center">CSML: The Domain-Specific Programming Language & Engine for Conversational AI</h1>
  • hightopics#2
    Add 'conversational-ai' and 'dsl' to repository topics

    Why:

    CURRENT
    chatbot, csml, interpreter, language, programming-language, rust
    COPY-PASTE FIX
    chatbot, csml, interpreter, language, programming-language, rust, conversational-ai, dsl
  • mediumreadme#3
    Refine the README's introductory paragraph to emphasize maintainability and robustness for conversational AI

    Why:

    CURRENT
    CSML (Conversational Standard Meta Language) is both a domain-specific programming language and chatbot engine, designed to make it easy to develop complex chatbots.
    COPY-PASTE FIX
    CSML (Conversational Standard Meta Language) is a powerful domain-specific programming language and chatbot engine, designed to simplify the development of complex, robust, and maintainable conversational AI applications.

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 CSML-by-Clevy/csml-engine
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
RasaHQ/rasa
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. RasaHQ/rasa · recommended 2×
  2. botpress/botpress · recommended 2×
  3. explosion/spaCy · recommended 1×
  4. nltk/nltk · recommended 1×
  5. tensorflow/tensorflow · recommended 1×
  • CATEGORY QUERY
    What is a good programming language for building complex, maintainable conversational AI applications?
    you: not recommended
    AI recommended (in order):
    1. Rasa (RasaHQ/rasa)
    2. spaCy (explosion/spaCy)
    3. NLTK (nltk/nltk)
    4. TensorFlow (tensorflow/tensorflow)
    5. PyTorch (pytorch/pytorch)
    6. Spring Framework (spring-projects/spring-framework)
    7. Stanford CoreNLP (stanfordnlp/CoreNLP)
    8. Apache OpenNLP (apache/opennlp)
    9. Botpress (botpress/botpress)
    10. Microsoft Bot Framework (microsoft/botframework-sdk)
    11. Natural (NaturalNode/natural)
    12. Azure Cognitive Services

    AI recommended 12 alternatives but never named CSML-by-Clevy/csml-engine. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an easy-to-use domain-specific language for developing robust chatbot logic efficiently.
    you: not recommended
    AI recommended (in order):
    1. Rasa (RasaHQ/rasa)
    2. Botpress (botpress/botpress)
    3. Dialogflow
    4. Cognigy.AI
    5. Microsoft Bot Framework Composer (microsoft/BotFramework-Composer)
    6. Voiceflow

    AI recommended 6 alternatives but never named CSML-by-Clevy/csml-engine. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 CSML-by-Clevy/csml-engine?
    pass
    AI named CSML-by-Clevy/csml-engine explicitly

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

  • If a team adopts CSML-by-Clevy/csml-engine in production, what risks or prerequisites should they evaluate first?
    pass
    AI named CSML-by-Clevy/csml-engine 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 CSML-by-Clevy/csml-engine solve, and who is the primary audience?
    pass
    AI did not name CSML-by-Clevy/csml-engine — 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?

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CSML-by-Clevy/csml-engine — 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