RRepoGEO

REPOGEO REPORT · LITE

aiwaves-cn/agents

Default branch master · commit e8c4e3c2 · scanned 6/25/2026, 10:12:58 AM

GitHub: 5,933 stars · 482 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
28 /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
2 / 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 aiwaves-cn/agents, 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
  • highhomepage#1
    Add homepage URL to repository About section

    Why:

    COPY-PASTE FIX
    https://aiwaves-cn.github.io/agents/
  • highreadme#2
    Add a clarifying sentence to the 'Overview' section to differentiate from RL

    Why:

    CURRENT
    ## 🌟Overview
    
    Agent symbolic learning is a systematic framework for training language agents...
    COPY-PASTE FIX
    ## 🌟Overview
    
    Agents 2.0 introduces a novel approach to training and evaluating language agents through symbolic learning, distinct from traditional reinforcement learning methods. Agent symbolic learning is a systematic framework for training language agents...
  • mediumtopics#3
    Add more specific topics to highlight symbolic learning and agent training

    Why:

    CURRENT
    autonomous-agents, language-model, llm
    COPY-PASTE FIX
    autonomous-agents, language-model, llm, symbolic-learning, agent-training, agent-evaluation, data-centric-ai

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 aiwaves-cn/agents
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
RLlib
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. RLlib · recommended 2×
  2. AutoGPT · recommended 1×
  3. LangChain · recommended 1×
  4. LlamaIndex · recommended 1×
  5. OpenAI API · recommended 1×
  • CATEGORY QUERY
    How can I build and train self-evolving autonomous language agents?
    you: not recommended
    AI recommended (in order):
    1. AutoGPT
    2. LangChain
    3. LlamaIndex
    4. OpenAI API
    5. Hugging Face Transformers
    6. PEFT
    7. RLlib
    8. DeepMind's AlphaCode
    9. Google DeepMind's Gemini

    AI recommended 9 alternatives but never named aiwaves-cn/agents. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source frameworks exist for data-centric agent learning and evaluation?
    you: not recommended
    AI recommended (in order):
    1. RLlib
    2. Stable Baselines3
    3. CleanRL
    4. OpenSpiel
    5. Tianshou
    6. Acme
    7. DI-engine

    AI recommended 7 alternatives but never named aiwaves-cn/agents. 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 aiwaves-cn/agents?
    pass
    AI did not name aiwaves-cn/agents — likely talking about a different project

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

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

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

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aiwaves-cn/agents — 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