RRepoGEO

REPOGEO REPORT · LITE

git-ai-project/git-ai

Default branch main · commit 5a3a97f6 · scanned 6/21/2026, 2:51:49 AM

GitHub: 2,104 stars · 204 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
33 /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
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 git-ai-project/git-ai, 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 to clarify core purpose and differentiate from AI code generation

    Why:

    CURRENT
    Git AI is an open source git extension that tracks the AI-generated code in your repositories. After installing the extension, every line of AI code is linked to the **agent, model, and prompts** that generated it — so you never lose the intent, requirements, and architecture decisions behind your code.
    COPY-PASTE FIX
    Git AI is an open source git extension that **tracks and audits** the AI-generated code in your repositories. Unlike AI code generation tools, git-ai focuses on providing **provenance and accountability** for every AI-written line, linking it to the **agent, model, and prompts** that generated it. This ensures you never lose the intent, requirements, and architecture decisions behind your code.
  • mediumtopics#2
    Add more specific topics to reinforce the project's unique niche

    Why:

    CURRENT
    ai, ai-blame, coding-agents
    COPY-PASTE FIX
    ai, ai-blame, coding-agents, ai-code-auditing, code-provenance, llm-ops, ai-governance
  • lowabout#3
    Refine the 'About' description for greater clarity on tracking and auditing

    Why:

    CURRENT
    A Git extension for tracking the AI-generated code in your repos
    COPY-PASTE FIX
    A Git extension for tracking and auditing AI-generated code in your repositories, providing clear provenance for every AI-written line.

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 git-ai-project/git-ai
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 1 of 2 queries
COMPETITOR LEADERBOARD
  1. GitHub Copilot · recommended 1×
  2. Tabnine · recommended 1×
  3. CodeWhisperer · recommended 1×
  4. Gerrit Code Review · recommended 1×
  5. Review Board · recommended 1×
  • CATEGORY QUERY
    How can I track AI-generated code contributions within my Git repositories?
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot
    2. Tabnine
    3. CodeWhisperer
    4. Gerrit Code Review
    5. Review Board
    6. SonarQube
    7. ESLint
    8. Pylint
    9. GitLab
    10. GitHub
    11. Atlassian Bitbucket
    12. GitPython
    13. git log
    14. grep

    AI recommended 14 alternatives but never named git-ai-project/git-ai. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help identify AI-written code lines and their original prompts in git history?
    you: not recommended
    AI recommended (in order):
    1. Git Blame
    2. Git Log
    3. Moss
    4. Checkmarx Codebashing
    5. Black Duck by Synopsys
    6. VS Code
    7. GitHub Copilot Chat
    8. JetBrains IDEs
    9. JetBrains AI Assistant
    10. GitHub Pull Requests
    11. GitLab Merge Requests
    12. Crucible

    AI recommended 12 alternatives but never named git-ai-project/git-ai. 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 git-ai-project/git-ai?
    pass
    AI did not name git-ai-project/git-ai — 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 git-ai-project/git-ai in production, what risks or prerequisites should they evaluate first?
    pass
    AI named git-ai-project/git-ai 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 git-ai-project/git-ai solve, and who is the primary audience?
    pass
    AI named git-ai-project/git-ai explicitly

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

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  • Brand-free category queries5 vs 2 in Lite
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