RRepoGEO

REPOGEO REPORT · LITE

cclank/Hermes-Wiki

Default branch master · commit 05f3fc27 · scanned 6/8/2026, 8:48:25 PM

GitHub: 534 stars · 67 forks

AI VISIBILITY SCORE
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
1 / 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 cclank/Hermes-Wiki, 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
    Clarify repo's purpose as architecture documentation, not a framework or wiki software

    Why:

    CURRENT
    > 基于 Nous Research Hermes Agent 源码的深度架构文档。
> 所有页面均经过**逐行源码验证**，确保准确性与时效性。
    COPY-PASTE FIX
    > 本仓库是 Nous Research Hermes Agent 源码的深度架构文档和知识库。它不是一个 AI 代理框架或 Wiki 软件，而是对 Hermes Agent 内部机制的逐行源码验证和详细解析，确保准确性与时效性。
  • hightopics#2
    Add relevant topics for categorization

    Why:

    COPY-PASTE FIX
    llm-agents, ai-agents, agent-architecture, documentation, knowledge-base, llm-wiki, nous-research, hermes-agent, source-code-analysis
  • highlicense#3
    Add a standard open-source license file

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root containing the text of the MIT License.

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 cclank/Hermes-Wiki
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 1×
  2. run-llama/llama_index · recommended 1×
  3. microsoft/semantic-kernel · recommended 1×
  4. deepset-ai/haystack · recommended 1×
  5. microsoft/autogen · recommended 1×
  • CATEGORY QUERY
    How to build an advanced AI agent system with sophisticated tool orchestration and multi-provider support?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. Microsoft Semantic Kernel (microsoft/semantic-kernel)
    4. Haystack (deepset-ai/haystack)
    5. AutoGen (microsoft/autogen)
    6. CrewAI (joaomdmoura/crewai)
    7. Marvin (prefect-ai/marvin)

    AI recommended 7 alternatives but never named cclank/Hermes-Wiki. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are best practices for designing memory and prompt assembly systems in large language model agents?
    you: not recommended
    AI recommended (in order):
    1. Pinecone
    2. Weaviate
    3. Qdrant
    4. Chroma
    5. Redis
    6. PostgreSQL
    7. MongoDB
    8. LangChain
    9. LlamaIndex
    10. Jinja2
    11. Handlebars.js
    12. f-strings
    13. Guidance (Microsoft)
    14. Marvin (Prefect)
    15. Hugging Face Transformers

    AI recommended 15 alternatives but never named cclank/Hermes-Wiki. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 cclank/Hermes-Wiki?
    pass
    AI did not name cclank/Hermes-Wiki — 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 cclank/Hermes-Wiki in production, what risks or prerequisites should they evaluate first?
    pass
    AI named cclank/Hermes-Wiki 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 cclank/Hermes-Wiki solve, and who is the primary audience?
    pass
    AI did not name cclank/Hermes-Wiki — 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?

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cclank/Hermes-Wiki — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
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