RRepoGEO

REPOGEO REPORT · LITE

k8sgpt-ai/k8sgpt

Default branch main · commit fb246798 · scanned 5/16/2026, 8:11:25 AM

GitHub: 7,774 stars · 990 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 k8sgpt-ai/k8sgpt, 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 opening to highlight AI-driven diagnosis over generic monitoring

    Why:

    CURRENT
    `k8sgpt` is a tool for scanning your Kubernetes clusters, diagnosing, and triaging issues in simple English.
    COPY-PASTE FIX
    `k8sgpt` is an AI-powered diagnostic assistant for Kubernetes clusters, designed to scan, diagnose, and triage issues in simple English. Unlike traditional monitoring tools that provide raw data, k8sgpt leverages generative AI to interpret complex problems and offer actionable, human-readable explanations.
  • mediumtopics#2
    Add specific topics related to AI-driven Kubernetes diagnostics and explanations

    Why:

    CURRENT
    ai, devops, kubernetes, llama, openai, sre, tooling
    COPY-PASTE FIX
    ai, devops, kubernetes, llama, openai, sre, tooling, kubernetes-diagnosis, ai-troubleshooting, natural-language-explanation, llm-kubernetes
  • mediumcomparison#3
    Add a dedicated 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    ## How k8sgpt Compares to Observability Platforms

While tools like Datadog, Dynatrace, Prometheus, and Grafana excel at collecting metrics, logs, and traces, k8sgpt complements these by focusing on AI-driven interpretation. We don't replace your observability stack; instead, we act as an intelligent layer that translates raw data into clear, actionable diagnoses and suggested solutions, making complex Kubernetes issues understandable for everyone.

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 k8sgpt-ai/k8sgpt
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Dynatrace
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Dynatrace · recommended 2×
  2. Datadog · recommended 2×
  3. New Relic · recommended 2×
  4. Prometheus · recommended 2×
  5. Grafana · recommended 2×
  • CATEGORY QUERY
    How to leverage AI for automated diagnosis and troubleshooting of Kubernetes cluster issues?
    you: not recommended
    AI recommended (in order):
    1. Dynatrace
    2. Datadog
    3. New Relic
    4. Prometheus
    5. Grafana
    6. Thanos Ruler
    7. scikit-learn
    8. Prophet
    9. Alertmanager
    10. TensorFlow
    11. PyTorch
    12. cAdvisor
    13. Fluentd
    14. Fluent Bit
    15. Loki
    16. Kubeflow
    17. Logz.io

    AI recommended 17 alternatives but never named k8sgpt-ai/k8sgpt. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help SREs analyze Kubernetes cluster problems and provide simple English explanations?
    you: not recommended
    AI recommended (in order):
    1. Datadog
    2. New Relic
    3. Dynatrace
    4. Prometheus
    5. Grafana
    6. Alertmanager
    7. Splunk
    8. Komodor
    9. Robusta.dev

    AI recommended 9 alternatives but never named k8sgpt-ai/k8sgpt. 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 k8sgpt-ai/k8sgpt?
    pass
    AI named k8sgpt-ai/k8sgpt explicitly

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

  • If a team adopts k8sgpt-ai/k8sgpt in production, what risks or prerequisites should they evaluate first?
    pass
    AI named k8sgpt-ai/k8sgpt 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 k8sgpt-ai/k8sgpt solve, and who is the primary audience?
    pass
    AI named k8sgpt-ai/k8sgpt explicitly

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

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MARKDOWN (README)
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