RRepoGEO

REPOGEO REPORT · LITE

maxritter/pilot-shell

Default branch main · commit fc6c02ac · scanned 6/21/2026, 5:36:57 AM

GitHub: 1,756 stars · 148 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
40 /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
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 maxritter/pilot-shell, 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 H1 to specify its category as an AI agent framework

    Why:

    CURRENT
    ### How real engineers run Claude Code and Codex
    COPY-PASTE FIX
    ### Pilot Shell: The Production-Grade Framework for AI Code Generation Agents
  • mediumreadme#2
    Add a section to the README clarifying the project's license(s)

    Why:

    COPY-PASTE FIX
    ## License
This project is licensed under [Name of License 1] and [Name of License 2]. See the [LICENSE file](LICENSE) for details.
  • lowcomparison#3
    Add a 'Comparison' section to the README to differentiate from other AI agent frameworks

    Why:

    COPY-PASTE FIX
    ## Comparison to Other AI Agent Frameworks
Pilot Shell differentiates itself from general-purpose frameworks like LangChain and LlamaIndex by focusing specifically on production-grade, spec-driven AI code generation with Claude Code and Codex. Unlike broader frameworks, Pilot Shell enforces TDD, persistent memory, and quality gates out-of-the-box, providing a more opinionated and robust workflow for code-centric agents.

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 maxritter/pilot-shell
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. GitHub Actions · recommended 1×
  3. ESLint · recommended 1×
  4. Black · recommended 1×
  5. Prettier · recommended 1×
  • CATEGORY QUERY
    How to ensure AI code generation adheres to TDD and quality gates?
    you: not recommended
    AI recommended (in order):
    1. GitHub Copilot
    2. GitHub Actions
    3. ESLint
    4. Black
    5. Prettier
    6. SonarQube
    7. Bandit
    8. Codecov
    9. Coveralls
    10. Tabnine
    11. GitLab CI/CD
    12. Jenkins
    13. AWS CodeWhisperer
    14. AWS CodePipeline
    15. AWS CodeBuild
    16. Pytest
    17. JUnit
    18. SonarCloud
    19. Amazon Inspector
    20. Google Gemini Code Assist
    21. Google Cloud Build
    22. CodiumAI
    23. Husky
    24. pre-commit

    AI recommended 24 alternatives but never named maxritter/pilot-shell. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tools for building production-grade AI coding agents with persistent memory and planning?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. AutoGPT
    5. CrewAI
    6. Microsoft Guidance
    7. FastAPI
    8. Django
    9. PostgreSQL
    10. MongoDB
    11. OpenAI
    12. Anthropic

    AI recommended 12 alternatives but never named maxritter/pilot-shell. 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 maxritter/pilot-shell?
    pass
    AI named maxritter/pilot-shell explicitly

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

  • If a team adopts maxritter/pilot-shell in production, what risks or prerequisites should they evaluate first?
    pass
    AI named maxritter/pilot-shell 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 maxritter/pilot-shell solve, and who is the primary audience?
    pass
    AI named maxritter/pilot-shell explicitly

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

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maxritter/pilot-shell — 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