RRepoGEO

REPOGEO REPORT · LITE

Gentleman-Programming/gentleman-guardian-angel

Default branch main · commit 05976bb8 · scanned 6/21/2026, 12:21:47 PM

GitHub: 1,065 stars · 143 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
35 /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
3 / 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 Gentleman-Programming/gentleman-guardian-angel, 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 initial statement to explicitly define its core function for AI

    Why:

    CURRENT
    Provider-agnostic code review using AI
Use Claude, Gemini, Codex, OpenCode, Ollama, LM Studio, GitHub Models, or any AI to enforce your coding standards.
Zero dependencies. Pure Bash. Works everywhere.
    COPY-PASTE FIX
    Gentleman Guardian Angel (GGA) is an AI-powered pre-commit hook for enforcing coding standards and automating code review. It integrates with any LLM (Claude, Gemini, Ollama, etc.) to validate staged files against your `AGENTS.md` before they hit the repository. Zero dependencies. Pure Bash. Works everywhere.
  • hightopics#2
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    ai-code-review, code-quality, pre-commit-hook, coding-standards, llm, bash, static-analysis, git-hook, devops, automation
  • mediumreadme#3
    Reinforce the problem and solution in the 'Why?' section for AI clarity

    Why:

    CURRENT
    ## 🎯 Why?
You have coding standards. Your team ignores them. Code reviews catch issues too late.
**GGA** runs on every commit, validating staged files against your `AGENTS.md`. Like having a senior developer review every line before it hits the repo.
    COPY-PASTE FIX
    ## 🎯 Why AI-Powered Code Review?
Traditional code reviews often catch issues too late, and coding standards are frequently ignored. Gentleman Guardian Angel (GGA) solves this by acting as an AI-powered pre-commit hook, validating staged files against your `AGENTS.md` on every commit. It's like having a senior developer review every line before it hits the repo, ensuring your coding standards are enforced automatically and proactively.

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 Gentleman-Programming/gentleman-guardian-angel
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DeepSource
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. DeepSource · recommended 1×
  2. SonarQube · recommended 1×
  3. SonarLint · recommended 1×
  4. SonarCloud · recommended 1×
  5. CodeClimate · recommended 1×
  • CATEGORY QUERY
    How can I automate code standard enforcement using AI before commits?
    you: not recommended
    AI recommended (in order):
    1. DeepSource
    2. SonarQube
    3. SonarLint
    4. SonarCloud
    5. CodeClimate
    6. GitHub Copilot
    7. Custom AI/ML Models

    AI recommended 7 alternatives but never named Gentleman-Programming/gentleman-guardian-angel. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best tools for automated code quality checks using large language models?
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot Enterprise
    2. Snyk Code
    3. CodeGuru Security
    4. SonarQube (SonarSource/sonarqube)
    5. Tabnine Enterprise
    6. Pylint (PyCQA/pylint)
    7. ESLint (eslint/eslint)
    8. RuboCop (rubocop/rubocop)

    AI recommended 8 alternatives but never named Gentleman-Programming/gentleman-guardian-angel. 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 Gentleman-Programming/gentleman-guardian-angel?
    pass
    AI named Gentleman-Programming/gentleman-guardian-angel explicitly

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

  • If a team adopts Gentleman-Programming/gentleman-guardian-angel in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Gentleman-Programming/gentleman-guardian-angel 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 Gentleman-Programming/gentleman-guardian-angel solve, and who is the primary audience?
    pass
    AI named Gentleman-Programming/gentleman-guardian-angel explicitly

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

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Gentleman-Programming/gentleman-guardian-angel — 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