RRepoGEO

REPOGEO REPORT · LITE

looplj/axonhub

Default branch unstable · commit 45459698 · scanned 6/27/2026, 9:26:09 PM

GitHub: 4,444 stars · 556 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 looplj/axonhub, 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 direct problem statement to the README's opening

    Why:

    COPY-PASTE FIX
    AxonHub is an open-source AI Gateway designed to simplify and optimize your interactions with 100+ Large Language Models, providing built-in failover, load balancing, cost control, and end-to-end tracing.
  • hightopics#2
    Expand topics to include specific AI Gateway and LLM management terms

    Why:

    CURRENT
    agent, agents, ai, anthropic, anthropic-api, api-gateway, claude, claude-code, codex, cost-management, deepseek, gemini-api, llm, openai, opencode
    COPY-PASTE FIX
    agent, agents, ai, anthropic, anthropic-api, api-gateway, claude, claude-code, codex, cost-management, deepseek, gemini-api, llm, openai, opencode, llm-gateway, ai-proxy, llm-proxy, model-routing, failover, load-balancing, cost-optimization, api-management
  • mediumlicense#3
    Clarify the project's license in the README

    Why:

    COPY-PASTE FIX
    This project is licensed under [Specify License Name(s) here, e.g., 'a custom license based on X and Y']. Please see the LICENSE file for full details.

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 looplj/axonhub
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LiteLLM
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LiteLLM · recommended 2×
  2. Azure AI Studio · recommended 2×
  3. LangChain · recommended 1×
  4. LlamaIndex · recommended 1×
  5. OpenAI Evals · recommended 1×
  • CATEGORY QUERY
    How to simplify integration and management across many different large language model APIs?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. LiteLLM
    4. OpenAI Evals
    5. Azure AI Studio
    6. Google Cloud Vertex AI
    7. Hugging Face Transformers

    AI recommended 7 alternatives but never named looplj/axonhub. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a solution for load balancing, failover, and cost optimization across multiple LLM providers.
    you: not recommended
    AI recommended (in order):
    1. LiteLLM
    2. OpenRouter
    3. Azure AI Studio
    4. AWS Bedrock
    5. Nginx
    6. Envoy Proxy

    AI recommended 6 alternatives but never named looplj/axonhub. 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 looplj/axonhub?
    pass
    AI named looplj/axonhub explicitly

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

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

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

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looplj/axonhub — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite