RRepoGEO

REPOGEO REPORT · LITE

aurora-develop/aurora

Default branch main · commit b08b6f9c · scanned 7/1/2026, 12:32:08 PM

GitHub: 2,353 stars · 670 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 aurora-develop/aurora, 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 clearly state the project's purpose and disambiguate

    Why:

    CURRENT
    # AURORA
    COPY-PASTE FIX
    # AURORA: Free OpenAI-style API for ChatGPT Web Backend
  • mediumtopics#2
    Add more specific topics to improve category visibility

    Why:

    CURRENT
    chat2api, chatgpt, free, gpt
    COPY-PASTE FIX
    chat2api, chatgpt, free, gpt, openai-api-proxy, llm-api-gateway, image-generation, speech-api
  • lowhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://aurora-develop.github.io/aurora/api.html

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/aurora
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI API
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI API · recommended 2×
  2. Google AI Studio / Gemini API · recommended 1×
  3. Mistral AI · recommended 1×
  4. Hugging Face Inference API · recommended 1×
  5. Meta Llama 2 · recommended 1×
  • CATEGORY QUERY
    What are options for a free OpenAI-style API for advanced AI chat features?
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. Google AI Studio / Gemini API
    3. Mistral AI
    4. Hugging Face Inference API
    5. Meta Llama 2
    6. Perplexity AI
    7. Together AI
    8. Anyscale Endpoints

    AI recommended 8 alternatives but never named aurora-develop/aurora. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an API to integrate LLM chat, image generation, and speech processing.
    you: not recommended
    AI recommended (in order):
    1. OpenAI API
    2. Google Cloud AI
    3. Microsoft Azure AI Services
    4. Hugging Face
    5. Anthropic
    6. Stability AI
    7. ElevenLabs

    AI recommended 7 alternatives but never named aurora-develop/aurora. 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/aurora?
    pass
    AI named aurora-develop/aurora 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/aurora in production, what risks or prerequisites should they evaluate first?
    pass
    AI named aurora-develop/aurora 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/aurora solve, and who is the primary audience?
    pass
    AI named aurora-develop/aurora explicitly

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

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aurora-develop/aurora — RepoGEO report