RRepoGEO

REPOGEO REPORT · LITE

wanxingai/LightAgent

Default branch main · commit ca4ab4ba · scanned 5/28/2026, 8:37:21 AM

GitHub: 1,020 stars · 129 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 wanxingai/LightAgent, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ai-agent, agent-framework, multi-agent-system, llm, large-language-models, memory, skills, self-learning, openai, deepseek, qwen, python, open-source
  • mediumabout#2
    Update the repository description to highlight HITL capabilities

    Why:

    CURRENT
    LightAgent: Lightweight AI agent framework with memory, mcp & skill. Supports multi-agent collaboration, self-learning, and major LLMs (OpenAI/DeepSeek/Qwen). Open-source with MCP/SSE protocol integration.
    COPY-PASTE FIX
    LightAgent: Lightweight AI agent framework with memory, mcp & skill, emphasizing human-computer interaction and human-in-the-loop (HITL) capabilities. Supports multi-agent collaboration, self-learning, and major LLMs (OpenAI/DeepSeek/Qwen). Open-source with MCP/SSE protocol integration.
  • mediumhomepage#3
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    https://sufe-aiflm-lab.github.io/LightAgent/

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 wanxingai/LightAgent
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. AutoGen · recommended 1×
  3. LlamaIndex · recommended 1×
  4. Haystack · recommended 1×
  5. CrewAI · recommended 1×
  • CATEGORY QUERY
    Looking for an open-source framework to build AI agents with memory and multi-agent collaboration.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. AutoGen
    3. LlamaIndex
    4. Haystack
    5. CrewAI
    6. AgentVerse
    7. OpenDevin

    AI recommended 7 alternatives but never named wanxingai/LightAgent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a lightweight AI agent framework supporting self-learning and major large language models.
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. Haystack (deepset-ai/haystack)
    4. AutoGen (microsoft/autogen)
    5. CrewAI (joaomdmoura/crewai)
    6. LiteLLM (BerriAI/litellm)

    AI recommended 6 alternatives but never named wanxingai/LightAgent. 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 wanxingai/LightAgent?
    pass
    AI named wanxingai/LightAgent explicitly

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

  • If a team adopts wanxingai/LightAgent in production, what risks or prerequisites should they evaluate first?
    pass
    AI named wanxingai/LightAgent 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 wanxingai/LightAgent solve, and who is the primary audience?
    pass
    AI named wanxingai/LightAgent 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 wanxingai/LightAgent. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/wanxingai/LightAgent.svg)](https://repogeo.com/en/r/wanxingai/LightAgent)
HTML
<a href="https://repogeo.com/en/r/wanxingai/LightAgent"><img src="https://repogeo.com/badge/wanxingai/LightAgent.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

wanxingai/LightAgent — 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