RRepoGEO

REPOGEO REPORT · LITE

karminski/one-small-step

Default branch main · commit 1573d948 · scanned 6/29/2026, 11:33:16 AM

GitHub: 6,957 stars · 607 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
28 /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
2 / 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
  • highreadme#1
    Clarify the README's opening statement to prevent mis-categorization

    Why:

    CURRENT
    这是一个简单的技术科普教程项目, 主要聚焦于解释一些有趣的, 前沿的技术概念和原理. 每篇文章都力求在 5 分钟内阅读完成.目前更新速度👆, 力求每周不低于3篇
    COPY-PASTE FIX
    One Small Step 是一个专注于人工智能 (AI) 和大语言模型 (LLM) 前沿概念的快速技术科普教程项目。我们致力于用简洁明了的方式，在5分钟内解释复杂的原理，帮助读者轻松理解如 GGUF、推测性解码、Transformer 等核心技术。
  • hightopics#2
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    ai, llm, artificial-intelligence, large-language-models, machine-learning, deep-learning, transformer, technical-tutorials, popular-science, tech-education
  • mediumhomepage#3
    Add a homepage URL if an external site exists

    Why:

    COPY-PASTE FIX
    https://your-project-homepage.com

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
Towards Data Science
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Towards Data Science · recommended 1×
  2. Analytics Vidhya · recommended 1×
  3. IBM's AI Blog/Resources · recommended 1×
  4. Google AI Blog · recommended 1×
  5. 3Blue1Brown · recommended 1×
  • CATEGORY QUERY
    Where can I find quick, easy-to-understand explanations for cutting-edge AI concepts?
    you: not recommended
    AI recommended (in order):
    1. Towards Data Science
    2. Analytics Vidhya
    3. IBM's AI Blog/Resources
    4. Google AI Blog
    5. 3Blue1Brown
    6. Lex Fridman Podcast
    7. Machine Learning Mastery

    AI recommended 7 alternatives but never named karminski/one-small-step. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need short technical breakdowns of advanced large language model architectures and optimizations.
    you: not recommended
    AI recommended (in order):
    1. Transformer
    2. GPT-3
    3. BERT
    4. T5
    5. LoRA
    6. FlashAttention
    7. Mixtral 8x7B

    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 did not name karminski/one-small-step — 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?

  • 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