RRepoGEO

REPOGEO REPORT · LITE

kennethreitz/pytheory

Default branch master · commit 8faff51f · scanned 6/19/2026, 1:56:51 PM

GitHub: 1,620 stars · 83 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
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 kennethreitz/pytheory, 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
    Clarify or remove 'toy project' disclaimer in README

    Why:

    CURRENT
    *   "This is a toy project." *   "It's not meant to be used for anything serious." *   "It's just for fun."
    COPY-PASTE FIX
    Remove these lines from the README if the project is intended for practical use, or rephrase them to accurately reflect its current scope and capabilities.
  • mediumreadme#2
    Reposition README opening to highlight core differentiator and target audience

    Why:

    CURRENT
    <em>Explore music theory, compose multi-part arrangements, and hear them instantly — all in Python.</em>
    COPY-PASTE FIX
    <em>PyTheory offers a uniquely human-centric and Pythonic approach to music theory, enabling you to explore concepts, compose multi-part arrangements, and hear them instantly. It prioritizes elegance and ease of use for basic operations, making complex tasks accessible.</em>
  • lowcomparison#3
    Add a 'Comparison with Alternatives' section to the README

    Why:

    COPY-PASTE FIX
    ## Comparison with Alternatives

While libraries like Music21 and Mingus offer comprehensive features for musicology and composition, PyTheory focuses on a minimalist, Pythonic, and immediately audible experience. Our goal is to make exploring music theory and composing simple arrangements intuitive and fast, especially for those new to computational music or seeking rapid prototyping.

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 kennethreitz/pytheory
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Mingus
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Mingus · recommended 2×
  2. Music21 · recommended 1×
  3. MidiUtil · recommended 1×
  4. Pygame · recommended 1×
  5. Pymidi · recommended 1×
  • CATEGORY QUERY
    How can I programmatically compose multi-part musical arrangements and play them in Python?
    you: not recommended
    AI recommended (in order):
    1. Music21
    2. MidiUtil
    3. Pygame
    4. Pymidi
    5. Mingus
    6. Abjad

    AI recommended 6 alternatives but never named kennethreitz/pytheory. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What Python library helps explore music theory concepts like scales and chords programmatically?
    you: not recommended
    AI recommended (in order):
    1. music21
    2. Mido
    3. PyAudioAnalysis
    4. Pymusic
    5. Mingus
    6. python-acoustid

    AI recommended 6 alternatives but never named kennethreitz/pytheory. 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 kennethreitz/pytheory?
    pass
    AI did not name kennethreitz/pytheory — 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?

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

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

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kennethreitz/pytheory — 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