RRepoGEO

REPOGEO REPORT · LITE

anliyuan/Ultralight-Digital-Human

Default branch master · commit a892abe6 · scanned 6/30/2026, 8:23:07 AM

GitHub: 2,555 stars · 377 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
23 /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
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 anliyuan/Ultralight-Digital-Human, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    digital-human, real-time, mobile, lightweight, ai-model, computer-vision, speech-driven-animation, onnx-inference
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root with your chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0).
  • mediumreadme#3
    Clarify the README's opening to emphasize its nature as a developer-focused codebase

    Why:

    CURRENT
    A Ultralight Digital Human model can run on mobile devices in real time!!!
    COPY-PASTE FIX
    This repository provides a **developer-focused codebase** for an ultralight digital human model, specifically designed for real-time inference on mobile devices. It offers a foundational solution for integrating speech-driven animation into your applications.

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 anliyuan/Ultralight-Digital-Human
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Ready Player Me
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Ready Player Me · recommended 2×
  2. DeepMotion · recommended 2×
  3. Vroid Studio · recommended 2×
  4. MetaHuman Creator (Unreal Engine) · recommended 1×
  5. 8th Wall (now Niantic Lightship) · recommended 1×
  • CATEGORY QUERY
    Seeking a lightweight digital human solution capable of real-time mobile inference.
    you: not recommended
    AI recommended (in order):
    1. Ready Player Me
    2. MetaHuman Creator (Unreal Engine)
    3. DeepMotion
    4. 8th Wall (now Niantic Lightship)
    5. Tafi
    6. Vroid Studio
    7. Adobe Mixamo

    AI recommended 7 alternatives but never named anliyuan/Ultralight-Digital-Human. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Which real-time digital human models perform well on mobile with clear audio?
    you: not recommended
    AI recommended (in order):
    1. Ready Player Me
    2. MetaHuman
    3. Vroid Studio
    4. DeepMotion
    5. Mixamo

    AI recommended 5 alternatives but never named anliyuan/Ultralight-Digital-Human. 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 anliyuan/Ultralight-Digital-Human?
    pass
    AI did not name anliyuan/Ultralight-Digital-Human — 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 anliyuan/Ultralight-Digital-Human in production, what risks or prerequisites should they evaluate first?
    pass
    AI named anliyuan/Ultralight-Digital-Human 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 anliyuan/Ultralight-Digital-Human solve, and who is the primary audience?
    pass
    AI named anliyuan/Ultralight-Digital-Human 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 anliyuan/Ultralight-Digital-Human. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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anliyuan/Ultralight-Digital-Human — 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