RRepoGEO

REPOGEO REPORT · LITE

kagent-dev/kagent

Default branch main · commit e9e4e34d · scanned 6/18/2026, 4:16:53 AM

GitHub: 3,035 stars · 615 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)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 kagent-dev/kagent, 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
  • highabout#1
    Expand the 'about' description to highlight Kubernetes-native AI agent orchestration

    Why:

    CURRENT
    Cloud Native Agentic AI | Discord: https://bit.ly/kagentdiscord
    COPY-PASTE FIX
    A Kubernetes-native framework for building, deploying, and managing AI agents in cloud-native environments. | Discord: https://bit.ly/kagentdiscord
  • hightopics#2
    Add 'kubernetes' and 'ai-agents' to repository topics

    Why:

    CURRENT
    agents, ai, cncf, devops, mcp
    COPY-PASTE FIX
    agents, ai, cncf, devops, kubernetes, mcp, ai-agents, agent-orchestration
  • mediumreadme#3
    Refine README's opening paragraph to explicitly differentiate from MLOps platforms and generic agent frameworks

    Why:

    CURRENT
    kagent** is a Kubernetes native framework for building AI agents. Kubernetes is the most popular orchestration platform for running workloads, and **kagent** makes it easy to build, deploy and manage AI agents in Kubernetes. The **kagent** framework is designed to be easy to understand and use, and to provide a flexible and powerful way to build and manage AI agents.
    COPY-PASTE FIX
    kagent** is a Kubernetes-native framework for building, deploying, and managing AI agents. Unlike generic AI agent frameworks, **kagent** leverages Kubernetes' robust orchestration capabilities to treat AI agents as first-class, scalable workloads. It provides a powerful, cloud-native approach to agent lifecycle management, making it easy to build, deploy, and manage AI agents directly within Kubernetes, rather than relying on separate MLOps platforms or manual orchestration.

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 kagent-dev/kagent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Kubeflow
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Kubeflow · recommended 1×
  2. Kubeflow Pipelines · recommended 1×
  3. Jupyter Notebooks · recommended 1×
  4. KFServing · recommended 1×
  5. Katib · recommended 1×
  • CATEGORY QUERY
    How can I deploy and manage multiple AI agents efficiently on a Kubernetes cluster?
    you: not recommended
    AI recommended (in order):
    1. Kubeflow
    2. Kubeflow Pipelines
    3. Jupyter Notebooks
    4. KFServing
    5. Katib
    6. TFJob
    7. PyTorchJob
    8. KServe
    9. Triton Inference Server
    10. TorchServe
    11. ONNX Runtime
    12. Argo Workflows
    13. Prometheus
    14. Grafana
    15. Helm
    16. Istio
    17. Linkerd
    18. Ray

    AI recommended 18 alternatives but never named kagent-dev/kagent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What cloud-native framework simplifies building and orchestrating intelligent agents for production environments?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Microsoft Semantic Kernel
    3. LlamaIndex
    4. Haystack
    5. OpenAI Assistants API
    6. Google Cloud Vertex AI Agent Builder
    7. Amazon Bedrock Agents

    AI recommended 7 alternatives but never named kagent-dev/kagent. 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 kagent-dev/kagent?
    pass
    AI named kagent-dev/kagent explicitly

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

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

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

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kagent-dev/kagent — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite