RRepoGEO

REPOGEO REPORT · LITE

athena-team/athena-signal

Default branch master · commit fdf89dea · scanned 6/15/2026, 3:07:44 PM

GitHub: 560 stars · 202 forks

AI VISIBILITY SCORE
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
1 / 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 athena-team/athena-signal, 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
  • highabout#1
    Add a clear, concise description to the About section

    Why:

    COPY-PASTE FIX
    An open-source C/Python library for speech signal processing, including Acoustic Echo Cancellation (AEC), Noise Suppression (NS), and Direction Of Arrival (DOA).
  • mediumhomepage#2
    Add a homepage URL to the About section

    Why:

    COPY-PASTE FIX
    https://github.com/athena-team/athena-signal

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 athena-team/athena-signal
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
librosa/librosa
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. librosa/librosa · recommended 1×
  2. tyiannak/pyAudioAnalysis · recommended 1×
  3. astorfi/speechpy · recommended 1×
  4. pytorch/audio · recommended 1×
  5. scipy/scipy · recommended 1×
  • CATEGORY QUERY
    What open-source library provides speech signal processing algorithms for Python projects?
    you: not recommended
    AI recommended (in order):
    1. Librosa (librosa/librosa)
    2. PyAudioAnalysis (tyiannak/pyAudioAnalysis)
    3. SpeechPy (astorfi/speechpy)
    4. torchaudio (pytorch/audio)
    5. SciPy.signal (scipy/scipy)
    6. pydub (jiaaro/pydub)

    AI recommended 6 alternatives but never named athena-team/athena-signal. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a C-based library for acoustic echo cancellation and noise suppression in audio streams.
    you: not recommended
    AI recommended (in order):
    1. WebRTC Audio Processing Library

    AI recommended 1 alternative but never named athena-team/athena-signal. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 athena-team/athena-signal?
    pass
    AI did not name athena-team/athena-signal — 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 athena-team/athena-signal in production, what risks or prerequisites should they evaluate first?
    pass
    AI named athena-team/athena-signal 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 athena-team/athena-signal solve, and who is the primary audience?
    pass
    AI did not name athena-team/athena-signal — 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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athena-team/athena-signal — 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