RRepoGEO

REPOGEO REPORT · LITE

ed-donner/agents

Default branch main · commit 0fb280d5 · scanned 5/11/2026, 9:13:34 PM

GitHub: 4,954 stars · 4,237 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 ed-donner/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
  • highreadme#1
    Reposition README H1 to clarify it's a course repository

    Why:

    CURRENT
    ## Master AI Agentic Engineering - build autonomous AI Agents
    COPY-PASTE FIX
    ## Master AI Agentic Engineering: Course Repository to Build Autonomous AI Agents
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ai-agents, agentic-ai, ai-engineering, openai-agents, crewai, langgraph, autogen, multi-agent-systems, ai-course, educational-resource
  • mediumhomepage#3
    Add the course's official homepage URL

    Why:

    COPY-PASTE FIX
    [URL of the Complete Agentic AI Engineering Course]

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 ed-donner/agents
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. OpenAI API · recommended 1×
  3. Hugging Face Transformers · recommended 1×
  4. Pinecone · recommended 1×
  5. Weaviate · recommended 1×
  • CATEGORY QUERY
    How to develop and deploy autonomous AI agents for various applications?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. OpenAI API
    3. Hugging Face Transformers
    4. Pinecone
    5. Weaviate
    6. Docker
    7. Kubernetes
    8. AWS Lambda
    9. Google Cloud Functions
    10. Azure Functions
    11. Ray

    AI recommended 11 alternatives but never named ed-donner/agents. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are effective frameworks for building and orchestrating multi-agent AI systems?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. AutoGen
    3. CrewAI
    4. Haystack
    5. Mirascope
    6. SPADE

    AI recommended 6 alternatives but never named ed-donner/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 ed-donner/agents?
    pass
    AI named ed-donner/agents explicitly

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

  • If a team adopts ed-donner/agents in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ed-donner/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 ed-donner/agents solve, and who is the primary audience?
    pass
    AI named ed-donner/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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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite