RRepoGEO

REPOGEO REPORT · LITE

0xSero/ai-data-extraction

Default branch main · commit b7520c48 · scanned 6/8/2026, 7:07:45 AM

GitHub: 761 stars · 77 forks

AI VISIBILITY SCORE
17 /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
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 0xSero/ai-data-extraction, 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
    Reposition the README's opening paragraph to clarify its role

    Why:

    CURRENT
    Complete toolkit to extract ALL chat, agent, and code context data from AI coding assistants for machine learning training.
    COPY-PASTE FIX
    This toolkit is a specialized utility for developers and researchers to extract their complete interaction history and code context *from* AI coding assistants like Cursor, Codex, and Claude Code. It enables you to collect your personal AI assistant data for analysis, backup, or fine-tuning custom machine learning models.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ai-assistants, data-extraction, machine-learning, fine-tuning, code-context, chat-logs, cursor-ai, codex-ai, claude-code
  • mediumlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Add a LICENSE file to the repository root, choosing an appropriate open-source license such as MIT or Apache-2.0 to clarify usage rights.

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 0xSero/ai-data-extraction
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GitHub Copilot
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. GitHub Copilot · recommended 2×
  2. ChatGPT · recommended 1×
  3. OpenAI models · recommended 1×
  4. Google Bard · recommended 1×
  5. Gemini · recommended 1×
  • CATEGORY QUERY
    How can I extract my complete interaction history from different AI coding assistants?
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot
    2. ChatGPT
    3. OpenAI models
    4. Google Bard
    5. Gemini
    6. Google Takeout
    7. Microsoft Copilot
    8. Amazon CodeWhisperer
    9. Tabnine
    10. Llama 3
    11. Ollama
    12. Open WebUI
    13. LM Studio
    14. Jan
    15. Faraday.dev

    AI recommended 15 alternatives but never named 0xSero/ai-data-extraction. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help export code context and chat logs from developer AI for training models?
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot
    2. GitHub API
    3. OpenAI API
    4. CodeTour
    5. VS Code Extension API
    6. JetBrains Plugin Development Kit (PDK)
    7. Python's `logging` module
    8. Log4j
    9. Winston
    10. Chrome DevTools
    11. Firefox Developer Tools
    12. OBS Studio
    13. Tesseract OCR

    AI recommended 13 alternatives but never named 0xSero/ai-data-extraction. 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 0xSero/ai-data-extraction?
    pass
    AI did not name 0xSero/ai-data-extraction — 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 0xSero/ai-data-extraction in production, what risks or prerequisites should they evaluate first?
    pass
    AI named 0xSero/ai-data-extraction 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 0xSero/ai-data-extraction solve, and who is the primary audience?
    pass
    AI did not name 0xSero/ai-data-extraction — 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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0xSero/ai-data-extraction — 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