REPOGEO REPORT · LITE

logpai/logparser

Default branch main · commit d9d41807 · scanned 6/24/2026, 4:57:00 PM

GitHub: 1,981 stars · 581 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)

3 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/logparser, 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 Logparser's role as an algorithmic toolkit in the README intro

Why:

CURRENT

Logparser provides a machine learning toolkit and benchmarks for automated log parsing, which is a crucial step for structured log analytics. By applying logparser, users can automatically extract event templates from unstructured logs and convert raw log messages into a sequence of structured events.

COPY-PASTE FIX

Logparser is a comprehensive machine learning toolkit and benchmark suite specifically designed for **automated log parsing**. It offers **multiple, often unsupervised, algorithmic approaches to automatically infer structured event templates** from unstructured log messages. Unlike full log management platforms, Logparser focuses on providing the core parsing engine for researchers and engineers building custom log analytics, monitoring, or anomaly detection systems.

mediumhomepage#2
Add the repository URL as the homepage
Why:
COPY-PASTE FIX
```
https://github.com/logpai/logparser
```

lowlicense#3

Clarify the existing license(s) in the README

Why:

COPY-PASTE FIX

### License
Logparser is distributed under [License Name(s), e.g., Apache-2.0]. Please refer to the [LICENSE.md](LICENSE.md) file for full details on the applicable terms and conditions.

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/logparser

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Elasticsearch

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Elasticsearch · recommended 2×
Logstash · recommended 2×
Kibana · recommended 2×
Splunk · recommended 2×
Fluentd · recommended 2×

CATEGORY QUERY
How can I automatically extract structured events from my unstructured log files?
you: not recommended
AI recommended (in order):
1. Elasticsearch
2. Logstash
3. Kibana
4. Splunk
5. Fluentd
6. Fluent Bit
7. Grok Exporter
8. Prometheus
9. Python
10. loguru
11. pandas
12. Sematext Logs
AI recommended 12 alternatives but never named logpai/logparser. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What machine learning toolkit helps convert raw log messages into structured data for analytics?
you: not recommended
AI recommended (in order):
1. Elastic Stack
2. Logstash
3. Elasticsearch
4. Kibana
5. Splunk
6. Apache Flink
7. Apache Spark
8. Fluentd
9. Fluent Bit
10. Vector
11. Grok Debugger
12. Grok Constructor
13. Python
14. Go
15. Java
16. re module
17. pyparsing
AI recommended 17 alternatives but never named logpai/logparser. 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/logparser?
pass
AI named logpai/logparser 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/logparser in production, what risks or prerequisites should they evaluate first?
pass
AI named logpai/logparser 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/logparser solve, and who is the primary audience?
pass
AI named logpai/logparser explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of logpai/logparser. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/logpai/logparser.svg)](https://repogeo.com/en/r/logpai/logparser)

HTML

<a href="https://repogeo.com/en/r/logpai/logparser"><img src="https://repogeo.com/badge/logpai/logparser.svg" alt="RepoGEO" /></a>

Pro

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logpai/logparser — 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