RRepoGEO

REPOGEO REPORT · LITE

ExtensityAI/symbolicai

Default branch main · commit da28e257 · scanned 6/28/2026, 2:52:05 PM

GitHub: 1,734 stars · 91 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)

2 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 ExtensityAI/symbolicai, 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
  • highhomepage#1
    Add the project's documentation link as the repository homepage

    Why:

    COPY-PASTE FIX
    https://extensityai.gitbook.io/symbolicai
  • mediumtopics#2
    Expand repository topics to include framework and hybrid AI descriptors

    Why:

    CURRENT
    large-language-models, neurosymbolic-ai, probabilistic-programming
    COPY-PASTE FIX
    large-language-models, neurosymbolic-ai, probabilistic-programming, ai-framework, hybrid-ai, symbolic-reasoning, llm-orchestration

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 ExtensityAI/symbolicai
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 1×
  2. Neo4j · recommended 1×
  3. RDFLib/rdflib · recommended 1×
  4. pydantic/pydantic · recommended 1×
  5. sympy/sympy · recommended 1×
  • CATEGORY QUERY
    How to integrate symbolic AI capabilities with large language models in Python?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. Neo4j
    3. RDFLib (RDFLib/rdflib)
    4. Pydantic (pydantic/pydantic)
    5. SymPy (sympy/sympy)
    6. NLTK (nltk/nltk)
    7. spaCy (explosion/spaCy)
    8. PyKE (pyke/pyke)
    9. Prolog
    10. PySwip (yuce/pyswip)

    AI recommended 10 alternatives but never named ExtensityAI/symbolicai. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a flexible Python framework for building custom programmable LLM applications.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. Instructor
    5. Guidance
    6. LiteLLM
    7. Transformers

    AI recommended 7 alternatives but never named ExtensityAI/symbolicai. 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 ExtensityAI/symbolicai?
    pass
    AI named ExtensityAI/symbolicai explicitly

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

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

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

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ExtensityAI/symbolicai — 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