RRepoGEO

REPOGEO REPORT · LITE

frankmcsherry/blog

Default branch master · commit 99cfb162 · scanned 6/21/2026, 8:53:02 PM

GitHub: 2,113 stars · 179 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
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 frankmcsherry/blog, 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
  • highreadme#1
    Reposition the README opening to highlight technical content

    Why:

    CURRENT
    I am a researcher and computer scientist. I used to work in San Francisco, then I traveled a bit, and I'm now in NYC starting Materialize.io.
    COPY-PASTE FIX
    This is a research blog by Frank McSherry, exploring advanced topics in distributed systems, dataflow programming (Timely, Differential), Datalog, and columnar data processing. It offers detailed explanations and insights for researchers and engineers interested in these areas.
  • mediumreadme#2
    Add a license statement to the README

    Why:

    COPY-PASTE FIX
    All content in this repository is licensed under a Creative Commons Attribution 4.0 International License (CC-BY-4.0).

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 frankmcsherry/blog
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
apache/kafka
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. apache/kafka · recommended 2×
  2. souffle-lang/souffle · recommended 1×
  3. LogicBlox · recommended 1×
  4. Datomic · recommended 1×
  5. cozodb/cozodb · recommended 1×
  • CATEGORY QUERY
    Seeking advanced techniques for optimizing Datalog queries and relational programming performance.
    you: not recommended
    AI recommended (in order):
    1. Soufflé (souffle-lang/souffle)
    2. LogicBlox
    3. Datomic
    4. CozoDB (cozodb/cozodb)
    5. Differential Datalog (DDlog) (vmware/differential-datalog)
    6. Flora-2 / Ergo AI
    7. YASA (Yet Another Static Analyzer) (yasa-analyzer/yasa)

    AI recommended 7 alternatives but never named frankmcsherry/blog. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are effective strategies for high-performance, real-time data processing and analytics?
    you: not recommended
    AI recommended (in order):
    1. Apache Flink (apache/flink)
    2. Apache Kafka Streams (apache/kafka)
    3. Apache Spark Streaming (apache/spark)
    4. Apache Kafka (apache/kafka)
    5. RabbitMQ (rabbitmq/rabbitmq-server)
    6. Amazon Kinesis
    7. ClickHouse (ClickHouse/ClickHouse)
    8. Apache Druid (apache/druid)
    9. SingleStore
    10. Apache Ignite (apache/ignite)
    11. Redis (redis/redis)

    AI recommended 11 alternatives but never named frankmcsherry/blog. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 frankmcsherry/blog?
    pass
    AI named frankmcsherry/blog explicitly

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

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

    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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MARKDOWN (README)
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frankmcsherry/blog — 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