RRepoGEO

REPOGEO REPORT · LITE

MGdaasLab/WHartTest

Default branch master · commit 3b977774 · scanned 6/8/2026, 9:12:00 PM

GitHub: 930 stars · 125 forks

AI VISIBILITY SCORE
27 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 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 MGdaasLab/WHartTest, 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
  • highreadme#1
    Clarify production readiness and intended use in the security warning

    Why:

    CURRENT
    本项目（WHartTest）仅供学习与研究使用。
    COPY-PASTE FIX
    WHartTest 作为一个功能完备的 AI 驱动测试平台，旨在提升测试效率。鉴于 Skills 模块的系统执行权限，本项目的生产部署需严格遵循安全指南，尤其是在内网环境或受信任的私有网络中。对于学习与研究目的，用户可自由探索其功能。
  • highreadme#2
    Add a concise, benefit-oriented tagline to the README's opening

    Why:

    COPY-PASTE FIX
    Add the following sentence immediately after the H1: "WHartTest 是一款专为测试团队设计的 AI 驱动平台，通过自动化需求到测试用例的生成与管理，显著提升软件测试的效率与覆盖率。"
  • mediumtopics#3
    Expand topics to emphasize "platform," "LLM-powered," and "end-to-end" aspects

    Why:

    CURRENT
    ai-test-platform, ai-testing, automated-testing, browser-automation, intelligent-testing, test-case-generation
    COPY-PASTE FIX
    ai-test-platform, ai-testing, automated-testing, browser-automation, intelligent-testing, test-case-generation, llm-powered, test-automation-platform, end-to-end-testing, software-quality

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 MGdaasLab/WHartTest
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI GPT-4 / GPT-3.5 Turbo
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI GPT-4 / GPT-3.5 Turbo · recommended 1×
  2. huggingface/transformers · recommended 1×
  3. Azure OpenAI Service / Google Cloud AI Platform · recommended 1×
  4. Testsigma · recommended 1×
  5. Parasoft SOAtest/Virtualize · recommended 1×
  • CATEGORY QUERY
    How to automate test case generation from natural language requirements using AI?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4 / GPT-3.5 Turbo
    2. Hugging Face Transformers (huggingface/transformers)
    3. Azure OpenAI Service / Google Cloud AI Platform
    4. Testsigma
    5. Parasoft SOAtest/Virtualize
    6. NLTK (nltk/nltk)
    7. SpaCy (explosion/spaCy)

    AI recommended 7 alternatives but never named MGdaasLab/WHartTest. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are intelligent test automation platforms for improving software quality and coverage?
    you: not recommended
    AI recommended (in order):
    1. Cypress.io
    2. Playwright
    3. Testim.io
    4. Applitools Eyes
    5. Smartbear TestComplete
    6. Tricentis Tosca

    AI recommended 6 alternatives but never named MGdaasLab/WHartTest. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 MGdaasLab/WHartTest?
    pass
    AI did not name MGdaasLab/WHartTest — 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 MGdaasLab/WHartTest in production, what risks or prerequisites should they evaluate first?
    pass
    AI named MGdaasLab/WHartTest 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 MGdaasLab/WHartTest solve, and who is the primary audience?
    pass
    AI did not name MGdaasLab/WHartTest — 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?

Embed your GEO score

Drop this badge into the README of MGdaasLab/WHartTest. 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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MGdaasLab/WHartTest — RepoGEO report