RRepoGEO

REPOGEO REPORT · LITE

czl9707/build-your-own-openclaw

Default branch main · commit f45e79af · scanned 5/10/2026, 3:57:45 AM

GitHub: 1,590 stars · 286 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 czl9707/build-your-own-openclaw, 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 'OpenClaw' in README title and opening sentence

    Why:

    CURRENT
    # Build Your Own OpenClaw

A step-by-step tutorial to build your own AI agent, from a simple chat loop to a lightweight version of OpenClaw.
    COPY-PASTE FIX
    # Build Your Own OpenClaw: A Step-by-Step AI Agent Tutorial

A step-by-step tutorial to build your own AI agent, named OpenClaw, from a simple chat loop to a lightweight version of a sophisticated agent. This project focuses on software development for AI agents, not physical robotics.
  • mediumtopics#2
    Add more specific topics to emphasize 'from scratch' and 'tutorial'

    Why:

    CURRENT
    ai-agent, build-your-own-x, llm, python, tutorial
    COPY-PASTE FIX
    ai-agent, build-your-own-ai-agent, llm, python, tutorial, step-by-step-guide, agent-development, from-scratch
  • mediumreadme#3
    Add a section differentiating from high-level frameworks

    Why:

    COPY-PASTE FIX
    ## Why Build Your Own?

This tutorial teaches the fundamental concepts and implementation details of AI agents from scratch, without relying on high-level frameworks. While frameworks like LangChain or LlamaIndex provide powerful abstractions, this guide focuses on understanding the underlying mechanics by building each component yourself.

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 czl9707/build-your-own-openclaw
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Coursera
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Coursera · recommended 1×
  2. fast.ai · recommended 1×
  3. nltk/nltk · recommended 1×
  4. explosion/spaCy · recommended 1×
  5. NicolasHug/Surprise · recommended 1×
  • CATEGORY QUERY
    How can I learn to build a custom AI agent from scratch, step-by-step?
    you: not recommended
    AI recommended (in order):
    1. Coursera
    2. fast.ai
    3. NLTK (nltk/nltk)
    4. spaCy (explosion/spaCy)
    5. Surprise (NicolasHug/Surprise)
    6. Scikit-learn (scikit-learn/scikit-learn)
    7. Pandas (pandas-dev/pandas)
    8. NumPy (numpy/numpy)
    9. BeautifulSoup4 (crummy/BeautifulSoup)
    10. Requests (psf/requests)
    11. TensorFlow (tensorflow/tensorflow)
    12. PyTorch (pytorch/pytorch)
    13. Keras (keras-team/keras)
    14. XGBoost (dmlc/xgboost)
    15. LightGBM (microsoft/LightGBM)
    16. Matplotlib (matplotlib/matplotlib)
    17. Seaborn (mwaskom/seaborn)
    18. TensorBoard (tensorflow/tensorboard)
    19. Flask (pallets/flask)
    20. FastAPI (tiangolo/fastapi)
    21. Docker
    22. Gradio (gradio-app/gradio)
    23. Streamlit (streamlit/streamlit)
    24. OpenAI Gym (openai/gym)
    25. Stable Baselines3 (DLR-RM/stable-baselines3)
    26. Ray RLlib (ray-project/ray)

    AI recommended 26 alternatives but never named czl9707/build-your-own-openclaw. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a Python tutorial to develop an LLM agent with tools and memory.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. AutoGen
    5. OpenAI Python Library
    6. Transformers

    AI recommended 6 alternatives but never named czl9707/build-your-own-openclaw. 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 czl9707/build-your-own-openclaw?
    pass
    AI named czl9707/build-your-own-openclaw explicitly

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

  • If a team adopts czl9707/build-your-own-openclaw in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name czl9707/build-your-own-openclaw — 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 czl9707/build-your-own-openclaw solve, and who is the primary audience?
    pass
    AI did not name czl9707/build-your-own-openclaw — 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

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czl9707/build-your-own-openclaw — 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