RRepoGEO

REPOGEO REPORT · LITE

kijai/ComfyUI-WanVideoWrapper

Default branch main · commit d18cdb18 · scanned 5/18/2026, 7:38:55 PM

GitHub: 6,431 stars · 637 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 kijai/ComfyUI-WanVideoWrapper, 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
  • highabout#1
    Add a concise description to the repo's 'About' section

    Why:

    COPY-PASTE FIX
    ComfyUI wrapper nodes for efficient video processing and memory management using WanVideo and related models, optimized for generative AI video workflows.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    comfyui, comfyui-nodes, video-processing, generative-ai, ai-video, wanvideo, lora, vram-optimization
  • mediumreadme#3
    Reposition the README's opening to clearly state the project's core purpose

    Why:

    CURRENT
    # ComfyUI wrapper nodes for WanVideo and related models.

## Memory use update (again)
    COPY-PASTE FIX
    # ComfyUI-WanVideoWrapper: Efficient Video Processing & Memory Management for ComfyUI

This repository provides ComfyUI wrapper nodes for the WanVideo library and related models, designed to streamline video frame extraction, encoding, and memory optimization within generative AI video workflows. It focuses on VRAM efficiency and robust LoRA weight handling for large models.

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 kijai/ComfyUI-WanVideoWrapper
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Efficient KSampler
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Efficient KSampler · recommended 1×
  2. Advanced KSampler · recommended 1×
  3. WAS Node Suite · recommended 1×
  4. AnimateDiff · recommended 1×
  5. SVD · recommended 1×
  • CATEGORY QUERY
    How can I improve VRAM efficiency for video generation models within ComfyUI?
    you: not recommended
    AI recommended (in order):
    1. Efficient KSampler
    2. Advanced KSampler
    3. WAS Node Suite
    4. AnimateDiff
    5. SVD
    6. PyTorch
    7. GGUF
    8. AWQ
    9. GPTQ
    10. ESRGAN
    11. Real-ESRGAN
    12. SwinIR

    AI recommended 12 alternatives but never named kijai/ComfyUI-WanVideoWrapper. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help manage LoRA weights and memory offloading for large AI models?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face PEFT
    2. Hugging Face Accelerate
    3. bitsandbytes
    4. DeepSpeed
    5. PyTorch FSDP

    AI recommended 5 alternatives but never named kijai/ComfyUI-WanVideoWrapper. 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 kijai/ComfyUI-WanVideoWrapper?
    pass
    AI did not name kijai/ComfyUI-WanVideoWrapper — 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 kijai/ComfyUI-WanVideoWrapper in production, what risks or prerequisites should they evaluate first?
    pass
    AI named kijai/ComfyUI-WanVideoWrapper 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 kijai/ComfyUI-WanVideoWrapper solve, and who is the primary audience?
    pass
    AI named kijai/ComfyUI-WanVideoWrapper 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 kijai/ComfyUI-WanVideoWrapper. 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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Pro

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kijai/ComfyUI-WanVideoWrapper — 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