RRepoGEO

REPOGEO REPORT · LITE

apple/ml-mgie

Default branch main · commit 835af371 · scanned 6/22/2026, 11:07:49 PM

GitHub: 3,876 stars · 252 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
30 /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
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 apple/ml-mgie, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition README opening to clarify project type and audience

    Why:

    CURRENT
    # Guiding Instruction-based Image Editing via Multimodal Large Language Models
This repo contains the code for Guiding Instruction-based Image Editing via Multimodal Large Language Models (ICLR'24 Spotlight)
    COPY-PASTE FIX
    MGIE (Multimodal Large Language Model-Guided Image Editing) is a research project and codebase from ICLR'24 Spotlight. It provides an official implementation for researchers and developers to explore how MLLMs can interpret natural language instructions to guide and perform image editing.
  • highabout#2
    Add a concise 'About' description

    Why:

    COPY-PASTE FIX
    Official implementation for MGIE (Multimodal Large Language Model-Guided Image Editing), an ICLR'24 Spotlight project that uses MLLMs to derive expressive instructions and guide image manipulation.

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 apple/ml-mgie
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Adobe Photoshop
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Adobe Photoshop · recommended 2×
  2. Midjourney · recommended 2×
  3. DALL-E 3 · recommended 2×
  4. Stable Diffusion · recommended 2×
  5. Canva · recommended 2×
  • CATEGORY QUERY
    How can I edit images using natural language instructions without needing detailed masks or descriptions?
    you: not recommended
    AI recommended (in order):
    1. Adobe Photoshop
    2. Midjourney
    3. DALL-E 3
    4. Stable Diffusion
    5. Canva
    6. Clipdrop
    7. RunwayML

    AI recommended 7 alternatives but never named apple/ml-mgie. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help improve image editing control by generating expressive instructions from brief commands?
    you: not recommended
    AI recommended (in order):
    1. Adobe Photoshop
    2. Midjourney
    3. Stable Diffusion
    4. DALL-E 3
    5. RunwayML
    6. Canva

    AI recommended 6 alternatives but never named apple/ml-mgie. 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 apple/ml-mgie?
    pass
    AI named apple/ml-mgie explicitly

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

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

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

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MARKDOWN (README)
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HTML
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apple/ml-mgie — 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