RRepoGEO

REPOGEO REPORT · LITE

marsupialtail/quokka

Default branch master · commit 1caf62e8 · scanned 5/30/2026, 3:57:00 PM

GitHub: 1,192 stars · 63 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 marsupialtail/quokka, 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
    Move 'What is Quokka?' to the top of the README

    Why:

    CURRENT
    The current README places 'What is Quokka?' after a large centered block, showcases, and a blog post announcement.
    COPY-PASTE FIX
    Move the existing 'What is Quokka?' section, starting with 'In technical terms, Quokka is a **push-based distributed query engine with lineage-based fault tolerance**.', to immediately follow the main tagline 'Making data lakes work for time series.' at the top of the README.
  • mediumabout#2
    Refine the repository description for clarity

    Why:

    CURRENT
    Making data lake work for time series
    COPY-PASTE FIX
    A push-based distributed query engine for efficient, custom stateful and windowed computation over terabytes of historical time series data in Python data lakes.
  • mediumreadme#3
    Add a comparison section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, perhaps titled 'Quokka vs. Alternatives' or 'Why Quokka?', that explicitly outlines its advantages and differences compared to tools like Spark, Dask, or Flink for time series data processing.

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 marsupialtail/quokka
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Apache Spark
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Apache Spark · recommended 1×
  2. PySpark · recommended 1×
  3. Delta Lake · recommended 1×
  4. Dask · recommended 1×
  5. Parquet · recommended 1×
  • CATEGORY QUERY
    How to efficiently process large time series datasets in a Python data lake environment?
    you: not recommended
    AI recommended (in order):
    1. Apache Spark
    2. PySpark
    3. Delta Lake
    4. Dask
    5. Parquet
    6. ORC
    7. Polars
    8. Apache Arrow
    9. ClickHouse
    10. clickhouse-driver
    11. clickhouse-connect
    12. TimescaleDB
    13. psycopg2
    14. SQLAlchemy

    AI recommended 14 alternatives but never named marsupialtail/quokka. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a faster distributed ETL framework for MLOps on petabyte-scale data lakes than Spark?
    you: not recommended
    AI recommended (in order):
    1. Dask (dask/dask)
    2. Ray (ray-project/ray)
    3. Apache Flink (apache/flink)
    4. ClickHouse (ClickHouse/ClickHouse)
    5. Trino (trino-project/trino)
    6. Databricks Photon Engine
    7. Snowflake
    8. Google BigQuery
    9. Amazon Redshift

    AI recommended 9 alternatives but never named marsupialtail/quokka. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 marsupialtail/quokka?
    pass
    AI named marsupialtail/quokka explicitly

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

  • If a team adopts marsupialtail/quokka in production, what risks or prerequisites should they evaluate first?
    pass
    AI named marsupialtail/quokka 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 marsupialtail/quokka solve, and who is the primary audience?
    pass
    AI named marsupialtail/quokka 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 marsupialtail/quokka. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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  • Brand-free category queries5 vs 2 in Lite
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