RRepoGEO

REPOGEO REPORT · LITE

xerrors/Yuxi

Default branch main · commit dfb8688e · scanned 6/25/2026, 11:37:14 PM

GitHub: 5,763 stars · 829 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)

3 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 xerrors/Yuxi, 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 disambiguation statement to the README introduction

    Why:

    CURRENT
    The current README's '简介' section starts with '语析（Yuxi）是一个基于大模型的智能知识库与知识图谱智能体开发平台。'.
    COPY-PASTE FIX
    Insert the following sentence at the beginning of the '简介' section, right after the first sentence:
"**Please note:** Despite the repository owner name, Yuxi is a multi-tenant platform for building AI agents with integrated knowledge bases and graphs, and is *not* a Go error handling library or an API Gateway."
  • highabout#2
    Clarify the repository's identity in the 'About' description

    Why:

    CURRENT
    结合知识库、知识图谱管理的 多租户 Agent Harness 平台。 An agent harness that integrates a LightRAG knowledge base and knowledge graphs. Build with LangChain + Vue + FastAPI, support DeepAgents、MinerU PDF、Neo4j 、MCP.
    COPY-PASTE FIX
    Yuxi is a multi-tenant platform for building AI agents with integrated knowledge bases and graphs. It is *not* a Go error handling library or an API Gateway. This agent harness integrates a LightRAG knowledge base and knowledge graphs, built with LangChain + Vue + FastAPI, supporting DeepAgents、MinerU PDF、Neo4j 、MCP.
  • mediumreadme#3
    Add a 'Key Features' section highlighting enterprise and multi-tenant capabilities

    Why:

    COPY-PASTE FIX
    Add a new section, for example, after '简介' and before '技术栈':
```
## Key Features for Enterprise AI Agents (核心优势)

*   **Multi-Tenant Agent Harness:** Centralized platform for managing multiple AI agents and users within an enterprise environment.
*   **Integrated Knowledge Management:** Seamlessly combines RAG retrieval, Milvus knowledge bases, and Neo4j knowledge graphs for comprehensive knowledge access.
*   **Advanced Agent Orchestration:** Leverages LangGraph for sophisticated multi-agent workflows, supporting DeepAgents, MCP, and custom skills.
*   **Intuitive User Experience:** Provides a ChatGPT-like interface for user interaction, delivering answers with source citations, knowledge graph reasoning, and deliverable outputs.
```

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 xerrors/Yuxi
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. Neo4j AuraDB · recommended 1×
  3. LlamaIndex · recommended 1×
  4. DataStax Astra DB · recommended 1×
  5. RAGStack · recommended 1×
  • CATEGORY QUERY
    Looking for a multi-tenant platform to build AI agents with integrated knowledge bases and graphs.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Neo4j AuraDB
    3. LlamaIndex
    4. DataStax Astra DB
    5. RAGStack
    6. Microsoft Azure AI Studio
    7. Azure Cosmos DB
    8. Google Cloud Vertex AI
    9. AWS Bedrock
    10. Amazon Neptune

    AI recommended 10 alternatives but never named xerrors/Yuxi. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to build an enterprise knowledge management system using RAG and intelligent LLM agents?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. OpenSearch (opensearch-project/OpenSearch)
    4. Elasticsearch (elastic/elasticsearch)
    5. Hugging Face Transformers (huggingface/transformers)
    6. Sentence Transformers (UKPLab/sentence-transformers)
    7. OpenAI API
    8. Azure OpenAI Service
    9. Anthropic Claude
    10. FastAPI (tiangolo/fastapi)
    11. Flask (pallets/flask)
    12. Kubernetes (kubernetes/kubernetes)
    13. Docker

    AI recommended 13 alternatives but never named xerrors/Yuxi. 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 xerrors/Yuxi?
    pass
    AI named xerrors/Yuxi explicitly

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

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

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

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xerrors/Yuxi — 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