RRepoGEO

REPOGEO REPORT · LITE

higress-group/himarket

Default branch main · commit 277bd627 · scanned 5/20/2026, 5:26:41 AM

GitHub: 1,157 stars · 149 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
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 higress-group/himarket, 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 specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    ai-marketplace, llm-ops, model-management, agent-platform, api-gateway, enterprise-ai, higress
  • mediumreadme#2
    Clarify the existing license in the README

    Why:

    COPY-PASTE FIX
    Add a section or line in the README, e.g., "License: This project is licensed under [Name of License 1] and [Name of License 2]. See the LICENSE file for full details."
  • lowhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://deepwiki.com/higress-group/himarket

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 higress-group/himarket
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Cloud Vertex AI
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Cloud Vertex AI · recommended 2×
  2. Azure Machine Learning · recommended 2×
  3. mlflow/mlflow · recommended 1×
  4. kubeflow/kubeflow · recommended 1×
  5. Hugging Face Hub · recommended 1×
  • CATEGORY QUERY
    How to build an internal AI capability marketplace for managing enterprise models and agents?
    you: not recommended
    AI recommended (in order):
    1. MLflow (mlflow/mlflow)
    2. Kubeflow (kubeflow/kubeflow)
    3. Hugging Face Hub
    4. Amazon SageMaker
    5. Google Cloud Vertex AI
    6. Domino Data Lab
    7. Azure Machine Learning

    AI recommended 7 alternatives but never named higress-group/himarket. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What platforms help publish and manage internal AI models as standardized API products?
    you: not recommended
    AI recommended (in order):
    1. Amazon SageMaker MLOps
    2. Azure Machine Learning
    3. Google Cloud Vertex AI
    4. Kubernetes
    5. Kubeflow
    6. Seldon Core
    7. KServe
    8. MLflow
    9. FastAPI
    10. Flask
    11. Databricks Lakehouse Platform
    12. Hugging Face Inference Endpoints

    AI recommended 12 alternatives but never named higress-group/himarket. 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 higress-group/himarket?
    pass
    AI named higress-group/himarket explicitly

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

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

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

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higress-group/himarket — 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