RRepoGEO

REPOGEO REPORT · LITE

edwko/OuteTTS

Default branch main · commit f5eac6e7 · scanned 6/29/2026, 8:56:49 PM

GitHub: 1,434 stars · 117 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
40 /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
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 edwko/OuteTTS, 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 the README's opening to clarify its core purpose

    Why:

    CURRENT
    The current README starts with "## OuteTTS" followed by links.
    COPY-PASTE FIX
    Add this sentence directly after the "## OuteTTS" heading: "OuteTTS is a versatile Python interface designed to simplify running and interacting with local text-to-speech models, including those in GGUF format, across various backends like Llama.cpp and Hugging Face Transformers."
  • mediumabout#2
    Enhance the repository description for clarity

    Why:

    CURRENT
    Interface for OuteTTS models.
    COPY-PASTE FIX
    A versatile Python interface for running local text-to-speech models, including GGUF, with support for Llama.cpp, Hugging Face Transformers, and other backends.
  • mediumtopics#3
    Add more specific topics to improve categorization

    Why:

    CURRENT
    gguf, llama, text-to-speech, transformers, tts
    COPY-PASTE FIX
    gguf, llama, text-to-speech, transformers, tts, python, inference, self-hosted, offline-tts, local-tts

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 edwko/OuteTTS
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Transformers
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 1×
  2. ESPnet · recommended 1×
  3. Coqui TTS · recommended 1×
  4. NVIDIA NeMo · recommended 1×
  5. Google Cloud Text-to-Speech API · recommended 1×
  • CATEGORY QUERY
    Looking for a versatile text-to-speech library compatible with various transformer models and backends.
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. ESPnet
    3. Coqui TTS
    4. NVIDIA NeMo
    5. Google Cloud Text-to-Speech API
    6. Amazon Polly

    AI recommended 6 alternatives but never named edwko/OuteTTS. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good options for running local text-to-speech models, especially GGUF format?
    you: not recommended
    AI recommended (in order):
    1. llama.cpp (ggerganov/llama.cpp)
    2. Piper (rhasspy/piper)
    3. Coqui TTS (coqui-ai/TTS)
    4. OpenVINO (openvinotoolkit/openvino)
    5. ONNX Runtime (microsoft/onnxruntime)
    6. Hugging Face transformers library (huggingface/transformers)

    AI recommended 6 alternatives but never named edwko/OuteTTS. 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 edwko/OuteTTS?
    pass
    AI named edwko/OuteTTS explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of edwko/OuteTTS. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/edwko/OuteTTS.svg)](https://repogeo.com/en/r/edwko/OuteTTS)
HTML
<a href="https://repogeo.com/en/r/edwko/OuteTTS"><img src="https://repogeo.com/badge/edwko/OuteTTS.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

edwko/OuteTTS — 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