RRepoGEO

REPOGEO REPORT · LITE

logpai/loglizer

Default branch master · commit ac67f972 · scanned 5/20/2026, 10:08:13 PM

GitHub: 1,416 stars · 439 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
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 logpai/loglizer, 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 Loglizer's specialized role in the README's opening

    Why:

    CURRENT
    Loglizer is a machine learning-based log analysis toolkit for automated anomaly detection.
    COPY-PASTE FIX
    Loglizer is a specialized machine learning-based log analysis toolkit for automated anomaly detection. It provides a suite of ML algorithms designed to integrate as a powerful analytical component within broader log processing pipelines, rather than serving as a full log management platform.
  • mediumhomepage#2
    Add a project homepage URL

    Why:

    COPY-PASTE FIX
    https://github.com/logpai
  • mediumreadme#3
    Add a 'Why Loglizer?' section to clarify its unique value proposition

    Why:

    COPY-PASTE FIX
    ## Why Loglizer?
Loglizer stands out as a dedicated toolkit focused purely on machine learning algorithms for log-based anomaly detection. Unlike comprehensive log management platforms (e.g., ELK Stack, Splunk, Prometheus) that handle collection, storage, and visualization, Loglizer provides the specialized analytical engine for identifying anomalies within your pre-processed log data. It's designed to be integrated as a powerful ML component into your existing log processing pipeline.

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 logpai/loglizer
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Elastic Stack
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Elastic Stack · recommended 2×
  2. Splunk · recommended 1×
  3. prometheus/prometheus · recommended 1×
  4. apache/flink · recommended 1×
  5. Datadog · recommended 1×
  • CATEGORY QUERY
    How can I automatically detect anomalies in system logs using machine learning techniques?
    you: not recommended
    AI recommended (in order):
    1. Elastic Stack
    2. Splunk
    3. Prometheus (prometheus/prometheus)
    4. Apache Flink (apache/flink)
    5. Datadog
    6. OpenSearch (opensearch-project/OpenSearch)
    7. Scikit-learn (scikit-learn/scikit-learn)

    AI recommended 7 alternatives but never named logpai/loglizer. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source tools provide intelligent fault diagnosis from aggregated log data?
    you: not recommended
    AI recommended (in order):
    1. Elastic Stack
    2. Grafana Loki
    3. Prometheus
    4. Apache Flink
    5. Apache Spark
    6. Opensearch
    7. Graylog

    AI recommended 7 alternatives but never named logpai/loglizer. 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 logpai/loglizer?
    pass
    AI named logpai/loglizer explicitly

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

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

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

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logpai/loglizer — 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