RRepoGEO

REPOGEO REPORT · LITE

SamuelQZQ/auto-coding-agent-demo

Default branch main · commit cdfb5a11 · scanned 6/22/2026, 7:53:14 AM

GitHub: 1,018 stars · 390 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
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 SamuelQZQ/auto-coding-agent-demo, 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 for discoverability

    Why:

    COPY-PASTE FIX
    ai-agent, auto-coding, full-stack, nextjs, llm-experiment, generative-ai, programming-agent
  • highlicense#2
    Add a LICENSE file

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT License) in the root of the repository.
  • highreadme#3
    Clarify the repository's purpose as an AI agent experiment in the README's opening

    Why:

    CURRENT
    本项目所有（100%）代码和提示词均由 AI 生成。运行前请自行审查，任何后果概不负责。
    COPY-PASTE FIX
    本项目是一个长达 10 小时的 AI 全自动编程实验，旨在探索和展示 AI Agent 从零开始构建一个完整全栈应用（hello-nextjs）的能力。所有（100%）代码和提示词均由 AI 生成。运行前请自行审查，任何后果概不负责。

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 SamuelQZQ/auto-coding-agent-demo
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Replit AI
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Replit AI · recommended 2×
  2. Vercel AI · recommended 1×
  3. GitHub Copilot Workspace · recommended 1×
  4. Durable.co · recommended 1×
  5. facebookresearch/codellama · recommended 1×
  • CATEGORY QUERY
    How can I use AI to generate entire full-stack applications, from frontend to backend?
    you: not recommended
    AI recommended (in order):
    1. Vercel AI
    2. GitHub Copilot Workspace
    3. Durable.co
    4. Code Llama (facebookresearch/codellama)
    5. Llama 3 (meta-llama/llama3)
    6. Replit AI
    7. Locofy.ai

    AI recommended 7 alternatives but never named SamuelQZQ/auto-coding-agent-demo. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best AI-powered tools for automating code generation across a full development lifecycle?
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot Enterprise
    2. AWS CodeWhisperer
    3. Tabnine Enterprise
    4. Google Gemini Code Assist
    5. CodiumAI (Codium-AI/CodiumAI-VSCode)
    6. Replit AI

    AI recommended 6 alternatives but never named SamuelQZQ/auto-coding-agent-demo. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 SamuelQZQ/auto-coding-agent-demo?
    pass
    AI named SamuelQZQ/auto-coding-agent-demo explicitly

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

  • If a team adopts SamuelQZQ/auto-coding-agent-demo in production, what risks or prerequisites should they evaluate first?
    pass
    AI named SamuelQZQ/auto-coding-agent-demo 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 SamuelQZQ/auto-coding-agent-demo solve, and who is the primary audience?
    pass
    AI did not name SamuelQZQ/auto-coding-agent-demo — 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?

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SamuelQZQ/auto-coding-agent-demo — 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