RRepoGEO

REPOGEO REPORT · LITE

kijai/ComfyUI-Florence2

Default branch main · commit 9ece3de9 · scanned 6/23/2026, 10:47:55 AM

GitHub: 1,706 stars · 141 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
28 /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
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-Florence2, 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 improve categorization

    Why:

    COPY-PASTE FIX
    ComfyUI, custom-node, Florence2, VLM, vision-language-model, image-captioning, object-detection, segmentation, visual-question-answering, DocVQA
  • highreadme#2
    Reposition the README's opening sentence to clarify its role as a ComfyUI custom node

    Why:

    CURRENT
    > Florence-2 is an advanced vision foundation model that uses a prompt-based approach to handle a wide range of vision and vision-language tasks.
    COPY-PASTE FIX
    > This repository offers a custom node for integrating the Florence-2 vision foundation model directly into ComfyUI, enabling advanced vision and vision-language tasks such as captioning, object detection, and segmentation.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    Add a relevant URL, such as a ComfyUI forum post, a demo video, or a project page, to the repository's homepage field.

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-Florence2
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
tensorflow/tensorflow
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. tensorflow/tensorflow · recommended 2×
  2. Google Cloud Vision AI · recommended 2×
  3. huggingface/transformers · recommended 1×
  4. gradio-app/gradio · recommended 1×
  5. streamlit/streamlit · recommended 1×
  • CATEGORY QUERY
    How to use advanced vision models for image captioning, detection, and segmentation in a UI?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers (huggingface/transformers)
    2. Gradio (gradio-app/gradio)
    3. Streamlit (streamlit/streamlit)
    4. OpenCV (opencv/opencv)
    5. ONNX Runtime (microsoft/onnxruntime)
    6. TensorFlow Lite (tensorflow/tensorflow)
    7. PyTorch (pytorch/pytorch)
    8. TensorFlow (tensorflow/tensorflow)
    9. Flask (pallets/flask)
    10. Django (django/django)
    11. Microsoft Azure Cognitive Services
    12. Google Cloud Vision AI
    13. Amazon Rekognition

    AI recommended 13 alternatives but never named kijai/ComfyUI-Florence2. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What solutions exist for visual question answering on document images to extract information?
    you: not recommended
    AI recommended (in order):
    1. Donut
    2. LayoutLMv3
    3. Pix2Struct
    4. UDOP
    5. OpenVQA
    6. Google Cloud Vision AI
    7. Amazon Textract

    AI recommended 7 alternatives but never named kijai/ComfyUI-Florence2. 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 kijai/ComfyUI-Florence2?
    pass
    AI named kijai/ComfyUI-Florence2 explicitly

    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-Florence2 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named kijai/ComfyUI-Florence2 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-Florence2 solve, and who is the primary audience?
    pass
    AI did not name kijai/ComfyUI-Florence2 — 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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kijai/ComfyUI-Florence2 — 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