RRepoGEO

REPOGEO REPORT · LITE

jd-opensource/JoyAI-Echo

Default branch main · commit 12d37046 · scanned 6/8/2026, 3:17:39 AM

GitHub: 869 stars · 55 forks

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 jd-opensource/JoyAI-Echo, 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
    video-generation, ai-video, long-video, audio-visual, deep-learning, computer-vision, generative-ai
  • highreadme#2
    Explicitly state 'AI video generation' in the README's opening

    Why:

    CURRENT
    Standalone, inference-only release for minute-level multi-shot audio-video generation with a distilled DMD generator, paired cross-modal memory, and story-level consistency.
    COPY-PASTE FIX
    JoyAI-Echo is an AI video generation framework, offering a standalone, inference-only release for minute-level multi-shot audio-video generation with a distilled DMD generator, paired cross-modal memory, and story-level consistency.
  • mediumreadme#3
    Clarify the project's license in the README

    Why:

    COPY-PASTE FIX
    ## License

This project is released under the terms specified in the [LICENSE](LICENSE) file. Please review the file for full details on usage and distribution.

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 jd-opensource/JoyAI-Echo
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Pika Labs
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Pika Labs · recommended 2×
  2. HeyGen · recommended 2×
  3. Adobe Premiere Pro · recommended 2×
  4. DaVinci Resolve · recommended 2×
  5. RunwayML Gen-2 · recommended 1×
  • CATEGORY QUERY
    How to generate consistent, minute-long videos from text or audio prompts?
    you: not recommended
    AI recommended (in order):
    1. RunwayML Gen-2
    2. Pika Labs
    3. HeyGen
    4. Synthesys AI Studio
    5. Stable Video Diffusion
    6. DeepMotion
    7. Adobe Premiere Pro
    8. DaVinci Resolve
    9. CapCut

    AI recommended 9 alternatives but never named jd-opensource/JoyAI-Echo. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help create multi-shot AI videos with strong temporal coherence and audio synchronization?
    you: not recommended
    AI recommended (in order):
    1. RunwayML
    2. Adobe Premiere Pro
    3. Pika Labs
    4. DaVinci Resolve
    5. Stable Diffusion
    6. ControlNet
    7. Deforum
    8. Midjourney
    9. EbSynth
    10. HeyGen
    11. Synthesys

    AI recommended 11 alternatives but never named jd-opensource/JoyAI-Echo. 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 jd-opensource/JoyAI-Echo?
    pass
    AI named jd-opensource/JoyAI-Echo explicitly

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

  • If a team adopts jd-opensource/JoyAI-Echo in production, what risks or prerequisites should they evaluate first?
    pass
    AI named jd-opensource/JoyAI-Echo 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 jd-opensource/JoyAI-Echo solve, and who is the primary audience?
    pass
    AI named jd-opensource/JoyAI-Echo 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 jd-opensource/JoyAI-Echo. 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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jd-opensource/JoyAI-Echo — 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
jd-opensource/JoyAI-Echo — RepoGEO report