RRepoGEO

REPOGEO REPORT · LITE

wecode-ai/Wegent

Default branch main · commit 76885761 · scanned 6/13/2026, 3:51:25 PM

GitHub: 582 stars · 103 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 wecode-ai/Wegent, 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 the README H1 to specify category

    Why:

    CURRENT
    # Wegent
    COPY-PASTE FIX
    # Wegent: An AI-Native Operating System for Intelligent Agent Teams
  • mediumtopics#2
    Add more specific topics for AI agent systems

    Why:

    CURRENT
    agent, ai, chatbot, chatgpt, claude-code, clawd, gemini, llm, notebooklm
    COPY-PASTE FIX
    agent, ai, chatbot, chatgpt, claude-code, clawd, gemini, llm, notebooklm, ai-workspace, agent-orchestration, multi-agent-system, ai-operating-system
  • mediumreadme#3
    Add a clarifying sentence to 'Why Wegent' section

    Why:

    CURRENT
    Wegent is a self-hostable AI workspace for managing chat, coding tasks, knowledge bases, automation, and local execution in one place.
    COPY-PASTE FIX
    Wegent is a self-hostable AI workspace for managing chat, coding tasks, knowledge bases, automation, and local execution in one place. Unlike general MLOps platforms or workflow orchestrators, Wegent focuses specifically on defining, organizing, and running intelligent agent teams within this workspace.

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 wecode-ai/Wegent
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
kubernetes/kubernetes
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. kubernetes/kubernetes · recommended 2×
  2. ray-project/ray · recommended 2×
  3. kubeflow/kubeflow · recommended 1×
  4. mlflow/mlflow · recommended 1×
  5. rancher/rancher · recommended 1×
  • CATEGORY QUERY
    How can I set up a self-hosted AI workspace for managing multiple intelligent agent teams?
    you: not recommended
    AI recommended (in order):
    1. Kubernetes (kubernetes/kubernetes)
    2. Kubeflow (kubeflow/kubeflow)
    3. MLflow (mlflow/mlflow)
    4. Kubeadm (kubernetes/kubernetes)
    5. Rancher (rancher/rancher)
    6. OpenShift (openshift/origin)
    7. Jupyter notebooks (jupyter/notebook)
    8. Kubeflow Pipelines (kubeflow/pipelines)
    9. KFServing (kserve/kserve)
    10. LangChain (langchain-ai/langchain)
    11. LlamaIndex (run-llama/llama_index)
    12. Docker Swarm (docker/swarm)
    13. HashiCorp Nomad (hashicorp/nomad)
    14. Hugging Face Transformers (huggingface/transformers)
    15. Hugging Face Diffusers (huggingface/diffusers)
    16. Hugging Face Accelerate (huggingface/accelerate)
    17. Hugging Face Hub
    18. Triton Inference Server (triton-inference-server/server)
    19. Ray (ray-project/ray)
    20. Ray Serve (ray-project/ray)
    21. JupyterHub (jupyterhub/jupyterhub)
    22. Dask (dask/dask)
    23. Prefect (PrefectHQ/prefect)
    24. NumPy (numpy/numpy)
    25. Pandas (pandas-dev/pandas)
    26. Scikit-learn (scikit-learn/scikit-learn)
    27. GitLab Enterprise
    28. GitHub Enterprise Server
    29. GitLab CI/CD
    30. GitHub Actions Self-Hosted Runners (actions/runner)
    31. Jenkins (jenkinsci/jenkins)
    32. Ansible (ansible/ansible)
    33. Terraform (hashicorp/terraform)

    AI recommended 33 alternatives but never named wecode-ai/Wegent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source platforms help develop and automate AI tasks with local execution capabilities?
    you: not recommended
    AI recommended (in order):
    1. MLflow
    2. Kubeflow
    3. Apache Airflow
    4. Metaflow
    5. DVC (Data Version Control)
    6. Rasa
    7. OpenCV

    AI recommended 7 alternatives but never named wecode-ai/Wegent. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 wecode-ai/Wegent?
    pass
    AI named wecode-ai/Wegent explicitly

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

  • If a team adopts wecode-ai/Wegent in production, what risks or prerequisites should they evaluate first?
    pass
    AI named wecode-ai/Wegent 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 wecode-ai/Wegent solve, and who is the primary audience?
    pass
    AI named wecode-ai/Wegent 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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wecode-ai/Wegent — 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