RRepoGEO

REPOGEO REPORT · LITE

karminski/one-small-step

Default branch main · commit 1573d948 · scanned 5/18/2026, 5:37:56 AM

GitHub: 6,935 stars · 608 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 karminski/one-small-step, 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 the repository

    Why:

    COPY-PASTE FIX
    ai, llm, large-language-models, machine-learning, deep-learning, transformer, quantization, speculative-decoding, gguf, tech-education, popular-science, tutorials, chinese
  • mediumreadme#2
    Add an explicit English tagline to the README's opening

    Why:

    CURRENT
    One Small Step
    COPY-PASTE FIX
    One Small Step: Quick Explanations for Advanced AI & LLM Concepts
  • lowhomepage#3
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    [Link to your project's main website or blog, e.g., a GitHub Pages site]

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 karminski/one-small-step
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google AI Blog
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Google AI Blog · recommended 1×
  2. Hugging Face Blog/Documentation · recommended 1×
  3. Towards Data Science · recommended 1×
  4. Distill.pub · recommended 1×
  5. jalammar/jalammar.github.io · recommended 1×
  • CATEGORY QUERY
    Where can I find quick explanations for advanced AI and large language model concepts?
    you: not recommended
    AI recommended (in order):
    1. Google AI Blog
    2. Hugging Face Blog/Documentation
    3. Towards Data Science
    4. Distill.pub
    5. Jay Alammar's Blog (jalammar/jalammar.github.io)
    6. OpenAI Blog

    AI recommended 6 alternatives but never named karminski/one-small-step. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    I need short, clear guides explaining modern large language model architecture and optimization techniques.
    you: not recommended
    AI recommended (in order):
    1. The Illustrated Transformer
    2. Attention Is All You Need
    3. Hugging Face Transformers (huggingface/transformers)
    4. Google Cloud
    5. DeepLearning.AI
    6. Efficient Transformers: A Survey
    7. PyTorch (pytorch/pytorch)

    AI recommended 7 alternatives but never named karminski/one-small-step. 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 karminski/one-small-step?
    pass
    AI named karminski/one-small-step explicitly

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

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

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

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karminski/one-small-step — 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