RRepoGEO

REPOGEO REPORT · LITE

aurora-develop/Duck2api

Default branch main · commit 27a6cbe8 · scanned 6/16/2026, 11:57:33 AM

GitHub: 742 stars · 166 forks

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 aurora-develop/Duck2api, 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
    Add a clear introductory sentence to the README

    Why:

    COPY-PASTE FIX
    This project provides a unified, OpenAI-compatible API endpoint to access various large language models (LLMs) like Claude, Llama, Mixtral, and GPT-4o-mini, leveraging DuckDuckGo's backend.
  • highabout#2
    Add a concise repository description

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    Provides a unified, OpenAI-compatible API endpoint to access various large language models (LLMs) like Claude, Llama, Mixtral, and GPT-4o-mini, leveraging DuckDuckGo's backend.
  • mediumtopics#3
    Expand repository topics for better category matching

    Why:

    CURRENT
    api, free, gpt
    COPY-PASTE FIX
    api, free, gpt, llm, proxy, openai-compatible, unified-api, claude, llama, mixtral, duckduckgo

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 aurora-develop/Duck2api
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
AnyScale Endpoints
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. AnyScale Endpoints · recommended 1×
  2. OpenRouter · recommended 1×
  3. BerriAI/litellm · recommended 1×
  4. langchain-ai/langchain · recommended 1×
  5. Hugging Face Inference API · recommended 1×
  • CATEGORY QUERY
    How can I access various large language models through a single, unified API endpoint?
    you: not recommended
    AI recommended (in order):
    1. AnyScale Endpoints
    2. OpenRouter
    3. LiteLLM (BerriAI/litellm)
    4. LangChain (langchain-ai/langchain)
    5. Hugging Face Inference API
    6. Azure AI Studio
    7. Google Cloud Vertex AI

    AI recommended 7 alternatives but never named aurora-develop/Duck2api. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Is there a free service to access different AI chat models using an OpenAI-compatible API?
    you: not recommended
    AI recommended (in order):
    1. OpenRouter.ai
    2. Anyscale Endpoints
    3. Perplexity AI (pplx-api)
    4. Together AI
    5. Fireworks AI
    6. DeepInfra

    AI recommended 6 alternatives but never named aurora-develop/Duck2api. 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 aurora-develop/Duck2api?
    pass
    AI named aurora-develop/Duck2api explicitly

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

  • If a team adopts aurora-develop/Duck2api in production, what risks or prerequisites should they evaluate first?
    pass
    AI named aurora-develop/Duck2api 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 aurora-develop/Duck2api solve, and who is the primary audience?
    pass
    AI named aurora-develop/Duck2api explicitly

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

Embed your GEO score

Drop this badge into the README of aurora-develop/Duck2api. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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HTML
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aurora-develop/Duck2api — 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