RRepoGEO

REPOGEO REPORT · LITE

chenryn/aiops-handbook

Default branch master · commit fa210a5d · scanned 6/29/2026, 3:02:03 PM

GitHub: 1,548 stars · 300 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
28 /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
2 / 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 chenryn/aiops-handbook, 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 README opening to emphasize 'curated resource collection' over 'product'

    Why:

    CURRENT
    AIOps 的论文、演讲、开源库的汇总手册。
    COPY-PASTE FIX
    This is a comprehensive, curated handbook and awesome list of AIOps papers, presentations, and open-source libraries, categorized by implementation scenarios.
  • mediumtopics#2
    Add more specific and descriptive topics

    Why:

    CURRENT
    aiops, anomalydetection, kpi
    COPY-PASTE FIX
    aiops, anomalydetection, kpi, awesome-list, research, papers, open-source-tools, handbook, machine-learning-ops
  • lowhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/chenryn/aiops-handbook

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 chenryn/aiops-handbook
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
IBM Cloud Pak for Watson AIOps
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. IBM Cloud Pak for Watson AIOps · recommended 1×
  2. IBM Instana · recommended 1×
  3. Splunk IT Service Intelligence (ITSI) · recommended 1×
  4. Splunk Observability Cloud · recommended 1×
  5. Dynatrace Davis · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive collection of resources for AIOps implementation?
    you: not recommended
    AI recommended (in order):
    1. IBM Cloud Pak for Watson AIOps
    2. IBM Instana
    3. Splunk IT Service Intelligence (ITSI)
    4. Splunk Observability Cloud
    5. Dynatrace Davis
    6. Moogsoft
    7. Magic Quadrant for AIOps Platforms
    8. Amazon CloudWatch
    9. Amazon DevOps Guru
    10. Amazon Sagemaker
    11. Cloud Monitoring
    12. Cloud Logging
    13. Cloud Trace

    AI recommended 13 alternatives but never named chenryn/aiops-handbook. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the leading open-source tools and research for KPI anomaly detection?
    you: not recommended
    AI recommended (in order):
    1. Prometheus (prometheus/prometheus)
    2. Alertmanager (prometheus/alertmanager)
    3. Grafana (grafana/grafana)
    4. Apache Superset (apache/superset)
    5. scikit-learn (scikit-learn/scikit-learn)
    6. statsmodels (statsmodels/statsmodels)
    7. OpenTSDB (OpenTSDB/opentsdb)
    8. Facebook Prophet (facebook/prophet)
    9. PyOD (yzhao062/pyod)
    10. ADTK (Novartis/adtk)

    AI recommended 10 alternatives but never named chenryn/aiops-handbook. 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 chenryn/aiops-handbook?
    pass
    AI did not name chenryn/aiops-handbook — likely talking about a different project

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

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

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

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chenryn/aiops-handbook — 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