RRepoGEO

REPOGEO REPORT · LITE

Jun-jie-Huang/awesome-LLM-AIOps

Default branch main · commit 3bb588d8 · scanned 6/20/2026, 1:42:32 AM

GitHub: 527 stars · 55 forks

AI VISIBILITY SCORE
22 /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
1 / 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 Jun-jie-Huang/awesome-LLM-AIOps, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • mediumreadme#1
    Explicitly state the repo's nature as a curated list in the README introduction

    Why:

    CURRENT
    A list of awesome academic researches and industrial materials about Large Language Model (LLM) and Artificial Intelligence for IT Operations (AIOps).
    COPY-PASTE FIX
    This repository is a curated, non-deployable list of awesome academic researches and industrial materials about Large Language Model (LLM) and Artificial Intelligence for IT Operations (AIOps).
  • lowhomepage#2
    Add the repository URL as the homepage

    Why:

    COPY-PASTE FIX
    https://github.com/Jun-jie-Huang/awesome-LLM-AIOps

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 Jun-jie-Huang/awesome-LLM-AIOps
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ServiceNow IT Service Management
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ServiceNow IT Service Management · recommended 2×
  2. Datadog Incident Management · recommended 1×
  3. Jira Service Management · recommended 1×
  4. PagerDuty Operations Cloud · recommended 1×
  5. Splunk IT Service Intelligence · recommended 1×
  • CATEGORY QUERY
    How can large language models enhance IT incident management and root cause analysis?
    you: not recommended
    AI recommended (in order):
    1. Datadog Incident Management
    2. ServiceNow IT Service Management
    3. Jira Service Management
    4. PagerDuty Operations Cloud
    5. Splunk IT Service Intelligence
    6. Dynatrace
    7. Gremlin
    8. ServiceNow IT Service Management
    9. Opsgenie
    10. Slack
    11. Microsoft Teams
    12. OpenAI's GPT
    13. Google's Gemini
    14. Statuspage
    15. Datadog Anomaly Detection
    16. New Relic Applied Intelligence
    17. Elastic Observability

    AI recommended 17 alternatives but never named Jun-jie-Huang/awesome-LLM-AIOps. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking resources on applying LLMs for automated log analysis and anomaly detection in operations.
    you: not recommended
    AI recommended (in order):
    1. Splunk ML Toolkit
    2. Elastic Stack
    3. Elasticsearch
    4. Kibana
    5. Logstash
    6. Eland
    7. LangChain
    8. LlamaIndex
    9. Grafana
    10. Loki
    11. Promtail
    12. Datadog
    13. Llama 3
    14. Mistral
    15. Falcon
    16. transformers
    17. pytorch
    18. tensorflow
    19. Cortex
    20. LogRhythm

    AI recommended 20 alternatives but never named Jun-jie-Huang/awesome-LLM-AIOps. 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 Jun-jie-Huang/awesome-LLM-AIOps?
    pass
    AI did not name Jun-jie-Huang/awesome-LLM-AIOps — 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 Jun-jie-Huang/awesome-LLM-AIOps in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Jun-jie-Huang/awesome-LLM-AIOps 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 Jun-jie-Huang/awesome-LLM-AIOps solve, and who is the primary audience?
    pass
    AI did not name Jun-jie-Huang/awesome-LLM-AIOps — 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?

Embed your GEO score

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Jun-jie-Huang/awesome-LLM-AIOps — 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
Jun-jie-Huang/awesome-LLM-AIOps — RepoGEO report