RRepoGEO

REPOGEO REPORT · LITE

ExtensityAI/symbolicai

Default branch main · commit c8d4bf2d · scanned 5/17/2026, 12:26:57 PM

GitHub: 1,716 stars · 86 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

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

OVERALL DIRECTION
  • highreadme#1
    Reposition README's H1 to clearly state it's a framework for neuro-symbolic AI

    Why:

    CURRENT
    # **SymbolicAI: A neuro-symbolic perspective on LLMs**
    COPY-PASTE FIX
    # **SymbolicAI: A Python Framework for Neuro-Symbolic AI with LLMs**
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://extensityai.gitbook.io/symbolicai
  • lowreadme#3
    Clarify the 'What is SymbolicAI?' opening sentence to emphasize its framework nature

    Why:

    CURRENT
    SymbolicAI is a **neuro-symbolic** framework, combining classical Python programming with the differentiable, programmable nature of LLMs in a way that actually feels natural in Python.
    COPY-PASTE FIX
    SymbolicAI is a **neuro-symbolic AI framework** designed to seamlessly integrate classical Python programming with the differentiable, programmable nature of LLMs, enabling developers to build robust and explainable AI systems that feel natural in Python.

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
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. DSPy · recommended 2×
  4. Neo4j · recommended 1×
  5. RDFLib · recommended 1×
  • CATEGORY QUERY
    How can I integrate symbolic reasoning with large language models in Python?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Neo4j
    3. RDFLib
    4. SymPy
    5. Prolog
    6. PySwip
    7. LlamaIndex
    8. DSPy
    9. NetworkX
    10. Pydantic
    11. PyReason
    12. SWI-Prolog

    AI recommended 12 alternatives but never named ExtensityAI/symbolicai. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a Python framework to build neurosymbolic AI systems with LLMs.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. DSPy
    5. PyKE
    6. Pytorch-Geometric

    AI recommended 6 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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MARKDOWN (README)
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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