RRepoGEO

REPOGEO REPORT · LITE

robusta-dev/krr

Default branch main · commit 4465a10b · scanned 5/14/2026, 11:02:18 PM

GitHub: 4,580 stars · 272 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 robusta-dev/krr, 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 KRR's role as a CLI tool and its relation to VPA in the 'About The Project' section.

    Why:

    CURRENT
    Robusta KRR (Kubernetes Resource Recommender) is a CLI tool for **optimizing resource allocation** in Kubernetes clusters. It gathers pod usage data from Prometheus and **recommends requests and limits** for CPU and memory. This **reduces costs and improves performance**.
    COPY-PASTE FIX
    Robusta KRR (Kubernetes Resource Recommender) is a powerful CLI tool that analyzes historical pod usage data from Prometheus (and other sources) to generate precise CPU and memory requests and limits. It offers a flexible, policy-driven alternative to Kubernetes Vertical Pod Autoscaler (VPA) for optimizing resource allocation, reducing costs, and improving performance.
  • mediumabout#2
    Populate the repository's homepage URL.

    Why:

    COPY-PASTE FIX
    Add the official KRR product page or documentation URL (e.g., `https://robusta.dev/krr`) to the repository's homepage field in the 'About' section.
  • mediumtopics#3
    Add more specific topics to improve categorization as a CLI recommendation tool.

    Why:

    CURRENT
    cost-control, cost-saving, finops, kubectl, kubernetes, metrics, monitoring, prometheus, rightsizing, vpa
    COPY-PASTE FIX
    cost-control, cost-saving, finops, kubectl, kubernetes, kubernetes-cli, kubernetes-optimization, metrics, monitoring, prometheus, resource-recommendations, rightsizing, vpa

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 robusta-dev/krr
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Prometheus
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Prometheus · recommended 2×
  2. Grafana · recommended 2×
  3. Goldilocks · recommended 2×
  4. Datadog · recommended 2×
  5. New Relic · recommended 2×
  • CATEGORY QUERY
    How to optimize Kubernetes pod resource requests and limits to reduce cloud costs?
    you: not recommended
    AI recommended (in order):
    1. Kubernetes Vertical Pod Autoscaler (VPA)
    2. Prometheus
    3. Grafana
    4. kube-state-metrics
    5. node-exporter
    6. Goldilocks
    7. KubeCost
    8. Datadog
    9. New Relic
    10. Dynatrace
    11. Kubecost (Open Source version)

    AI recommended 11 alternatives but never named robusta-dev/krr. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tool to get Kubernetes resource recommendations using Prometheus metrics for right-sizing?
    you: not recommended
    AI recommended (in order):
    1. Prometheus Adapter
    2. Vertical Pod Autoscaler (VPA)
    3. Goldilocks
    4. Kube-state-metrics
    5. Prometheus
    6. Grafana
    7. Robusta.dev
    8. Dynatrace
    9. Datadog
    10. New Relic

    AI recommended 10 alternatives but never named robusta-dev/krr. 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 robusta-dev/krr?
    pass
    AI named robusta-dev/krr explicitly

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

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

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

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