RRepoGEO

REPOGEO REPORT · LITE

yhy0/CHYing-agent

Default branch main · commit 0d2ee81f · scanned 6/19/2026, 11:57:30 AM

GitHub: 503 stars · 48 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 yhy0/CHYing-agent, 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 specific topics to improve categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    ai-agent, penetration-testing, cybersecurity, vulnerability-discovery, llm-agent, hackathon, autonomous-agent
  • highreadme#2
    Reposition the README H1 to clearly state the project's purpose

    Why:

    CURRENT
    # [TCH]腾讯云黑客松 第二届智能渗透挑战赛复盘
    COPY-PASTE FIX
    # CHYing-agent: LLM-powered AI Agent for Automated Penetration Testing and Cybersecurity Challenges
  • mediumreadme#3
    Add a concise introductory paragraph to the README

    Why:

    COPY-PASTE FIX
    CHYing-agent is an advanced AI agent framework designed to autonomously identify and exploit vulnerabilities in complex cybersecurity environments. Developed for the Tencent Cloud Hackathon's Intelligent Penetration Challenge, it leverages large language models (LLMs) to perform automated penetration testing, vulnerability discovery, and multi-step attack planning, making it a valuable resource for researchers and developers in AI-driven cybersecurity.

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 yhy0/CHYing-agent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
rapid7/metasploit-framework
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. rapid7/metasploit-framework · recommended 2×
  2. Shodan · recommended 1×
  3. Maltego · recommended 1×
  4. projectdiscovery/nuclei · recommended 1×
  5. greenbone/openvas · recommended 1×
  • CATEGORY QUERY
    How can I use AI agents for automated penetration testing and vulnerability discovery?
    you: not recommended
    AI recommended (in order):
    1. Shodan
    2. Maltego
    3. Nuclei (projectdiscovery/nuclei)
    4. OpenVAS (greenbone/openvas)
    5. Greenbone Vulnerability Management (GVM) (greenbone/gvm)
    6. Metasploit Framework (rapid7/metasploit-framework)
    7. Pocsuite3 (knownsec/pocsuite3)
    8. AFL++ (American Fuzzy Lop++) (google/AFLplusplus)
    9. Boofuzz (jtpereyda/boofuzz)
    10. OWASP Dependency-Check (jeremylong/DependencyCheck)
    11. Snyk
    12. LangChain (langchain-ai/langchain)
    13. LlamaIndex (run-llama/llama_index)

    AI recommended 13 alternatives but never named yhy0/CHYing-agent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking tools for building autonomous agents to solve cybersecurity challenges effectively.
    you: not recommended
    AI recommended (in order):
    1. OpenAI Gym (openai/gym)
    2. Farama Gymnasium (Farama-Foundation/Gymnasium)
    3. ML-Agents (Unity-Technologies/ml-agents)
    4. Pytorch (pytorch/pytorch)
    5. TensorFlow (tensorflow/tensorflow)
    6. Stable Baselines3 (DLR-RM/stable-baselines3)
    7. RLlib (ray-project/ray)
    8. Cuckoo Sandbox (cuckoosandbox/cuckoo)
    9. Metasploit Framework (rapid7/metasploit-framework)
    10. Scapy (secdev/scapy)

    AI recommended 10 alternatives but never named yhy0/CHYing-agent. 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 yhy0/CHYing-agent?
    pass
    AI named yhy0/CHYing-agent explicitly

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

  • If a team adopts yhy0/CHYing-agent in production, what risks or prerequisites should they evaluate first?
    pass
    AI named yhy0/CHYing-agent 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 yhy0/CHYing-agent solve, and who is the primary audience?
    pass
    AI named yhy0/CHYing-agent explicitly

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

Embed your GEO score

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MARKDOWN (README)
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yhy0/CHYing-agent — 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