RRepoGEO

REPOGEO REPORT · LITE

buildermethods/agent-os

Default branch main · commit cae8e664 · scanned 6/20/2026, 4:02:01 AM

GitHub: 4,915 stars · 772 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
28 /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
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 buildermethods/agent-os, 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 specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    ai-agents, code-standards, spec-driven-development, llm-development, developer-tools, code-generation, ai-workflow
  • highreadme#2
    Clarify the README's opening to state its category

    Why:

    CURRENT
    ## Agents that build the way you would

Agent OS helps you shape better specs, keeps agents aligned in a lightweight system that fits how you already build.
    COPY-PASTE FIX
    ## Agent OS: Aligning AI Agents with Your Codebase Standards for Spec-Driven Development

Agent OS is a system designed to help you enforce codebase standards and shape better specs when working with AI development agents. It keeps agents aligned with your team's conventions in a lightweight system that fits how you already build.
  • mediumreadme#3
    Add a "Why Agent OS?" section to highlight its unique differentiator

    Why:

    COPY-PASTE FIX
    ### Why Agent OS?

Unlike generic code quality tools or broad AI agent frameworks, Agent OS specifically focuses on extracting and injecting your team's unique codebase standards directly into the AI agent's workflow. This ensures that AI-generated code and specs are always aligned with your established conventions, leading to truly spec-driven development.

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 buildermethods/agent-os
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
SonarQube
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. SonarQube · recommended 2×
  2. DeepSource · recommended 1×
  3. CodeClimate Quality · recommended 1×
  4. Codiga · recommended 1×
  5. GitHub Copilot · recommended 1×
  • CATEGORY QUERY
    How can I enforce coding standards and improve spec generation using AI tools?
    you: not recommended
    AI recommended (in order):
    1. SonarQube
    2. DeepSource
    3. CodeClimate Quality
    4. Codiga
    5. GitHub Copilot
    6. ChatGPT
    7. GPT-4
    8. Claude 3
    9. OpenAPI Generator
    10. Speakeasy
    11. Tabnine

    AI recommended 11 alternatives but never named buildermethods/agent-os. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help align AI development agents with existing team coding conventions?
    you: not recommended
    AI recommended (in order):
    1. ESLint (eslint/eslint)
    2. Black (psf/black)
    3. Prettier (prettier/prettier)
    4. EditorConfig (editorconfig/editorconfig)
    5. Husky (typicode/husky)
    6. SonarQube
    7. GitHub Actions
    8. GitLab CI/CD
    9. Jenkins (jenkinsci/jenkins)
    10. Reviewdog (reviewdog/reviewdog)

    AI recommended 10 alternatives but never named buildermethods/agent-os. 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 buildermethods/agent-os?
    pass
    AI did not name buildermethods/agent-os — 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 buildermethods/agent-os in production, what risks or prerequisites should they evaluate first?
    pass
    AI named buildermethods/agent-os 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 buildermethods/agent-os solve, and who is the primary audience?
    pass
    AI named buildermethods/agent-os explicitly

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

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buildermethods/agent-os — 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