RRepoGEO

REPOGEO REPORT · LITE

wrtnlabs/autobe

Default branch main · commit 20ad5143 · scanned 5/23/2026, 12:07:42 PM

GitHub: 1,333 stars · 158 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 wrtnlabs/autobe, 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 AutoBE's role as an AI backend builder

    Why:

    CURRENT
    Describe your backend requirements in natural language through AutoBE's chat interface. AutoBE will analyze your requirements and build the backend application for you.
    COPY-PASTE FIX
    AutoBE is an AI agent that builds backend applications. Describe your backend requirements in natural language through AutoBE's chat interface, and it will analyze them and build the backend application for you.
  • mediumcomparison#2
    Add a 'Why AutoBE?' comparison section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, for example, after the initial description, titled "Why AutoBE? (vs. LLMs & Traditional Frameworks)". In this section, explain how AutoBE differs from:
*   **Generic LLMs (ChatGPT, Claude):** AutoBE provides structured, production-ready code with tests and docs, not just snippets.
*   **Backend Frameworks (NestJS, LoopBack):** AutoBE *generates* the application from natural language, requiring no manual coding to start, unlike frameworks where you code manually.
*   **Backend Generators (Amplication, JHipster):** AutoBE focuses on natural language input and AI-driven generation, potentially offering more flexibility or a different workflow.
  • lowtopics#3
    Add more specific topics for natural language code generation

    Why:

    CURRENT
    ai-coding-agent, all-in-one, automation, backend, generated-api, llm, nestia, nestjs, no-coding, no-coding-app, no-coding-tools, prisma, server, vibe-coding
    COPY-PASTE FIX
    ai-coding-agent, all-in-one, automation, backend, generated-api, llm, nestia, nestjs, no-coding, no-coding-app, no-coding-tools, prisma, server, vibe-coding, natural-language-processing, code-generation, nl2code, ai-code-generator

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 wrtnlabs/autobe
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Amplication
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Amplication · recommended 2×
  2. OpenAPI Generator · recommended 1×
  3. ChatGPT-4 · recommended 1×
  4. Google Gemini Advanced · recommended 1×
  5. Claude 3 Opus · recommended 1×
  • CATEGORY QUERY
    How can I quickly generate a TypeScript backend API from natural language descriptions?
    you: not recommended
    AI recommended (in order):
    1. OpenAPI Generator
    2. ChatGPT-4
    3. Google Gemini Advanced
    4. Claude 3 Opus
    5. Amplication
    6. Appsmith
    7. Code Llama
    8. GitHub Copilot
    9. Prisma
    10. TypeORM
    11. Replit AI

    AI recommended 11 alternatives but never named wrtnlabs/autobe. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools automate full backend server generation with robust testing and documentation?
    you: not recommended
    AI recommended (in order):
    1. LoopBack 4
    2. JHipster
    3. NestJS
    4. Hasura
    5. Amplication
    6. Strapi
    7. Serverless Framework

    AI recommended 7 alternatives but never named wrtnlabs/autobe. 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 wrtnlabs/autobe?
    pass
    AI named wrtnlabs/autobe explicitly

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

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

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

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wrtnlabs/autobe — 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