RRepoGEO

REPOGEO REPORT · LITE

charliedream1/ai_wiki

Default branch master · commit 347ae0d9 · scanned 6/14/2026, 6:52:54 PM

GitHub: 676 stars · 120 forks

AI VISIBILITY SCORE
22 /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
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 charliedream1/ai_wiki, 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 more specific topics to improve category recall

    Why:

    CURRENT
    ai, deep-learning, llm, pytorch
    COPY-PASTE FIX
    ai, deep-learning, llm, pytorch, full-stack-ai, ai-engineering, knowledge-base, problem-solving, large-language-models-guide, ai-resources
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a `LICENSE` file in the root of the repository with the text of your chosen open-source license (e.g., Apache-2.0, MIT, GPL-3.0).
  • mediumhomepage#3
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    Add `https://github.com/charliedream1/ai_wiki` (or a dedicated project site if one exists) to the repository's 'About' section.

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 charliedream1/ai_wiki
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Full Stack Deep Learning
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Full Stack Deep Learning · recommended 1×
  2. Made With ML · recommended 1×
  3. FastAPI · recommended 1×
  4. Docker · recommended 1×
  5. Designing Machine Learning Systems · recommended 1×
  • CATEGORY QUERY
    Where can I find practical guides for AI full-stack engineering problem-solving strategies?
    you: not recommended
    AI recommended (in order):
    1. Full Stack Deep Learning
    2. Made With ML
    3. FastAPI
    4. Docker
    5. Designing Machine Learning Systems
    6. Google's Machine Learning Crash Course
    7. Towards Data Science
    8. Databricks Blog
    9. AWS Machine Learning Blog
    10. SageMaker
    11. Lambda
    12. EC2

    AI recommended 12 alternatives but never named charliedream1/ai_wiki. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What resources offer comprehensive knowledge and practical cases for large model development?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers (huggingface/transformers)
    2. 🤗 Transformers Course
    3. Hugging Face Hub
    4. OpenAI API
    5. DeepLearning.AI
    6. PyTorch (pytorch/pytorch)
    7. TensorFlow (tensorflow/tensorflow)
    8. Keras (keras-team/keras)
    9. TensorFlow Hub
    10. "Attention Is All You Need"
    11. arXiv.org

    AI recommended 11 alternatives but never named charliedream1/ai_wiki. 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 charliedream1/ai_wiki?
    pass
    AI did not name charliedream1/ai_wiki — 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 charliedream1/ai_wiki in production, what risks or prerequisites should they evaluate first?
    pass
    AI named charliedream1/ai_wiki 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 charliedream1/ai_wiki solve, and who is the primary audience?
    pass
    AI did not name charliedream1/ai_wiki — 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 charliedream1/ai_wiki. 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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  • Brand-free category queries5 vs 2 in Lite
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