RRepoGEO

REPOGEO REPORT · LITE

SouravRoy-ETL/slothdb

Default branch main · commit 8180f215 · scanned 6/17/2026, 9:37:04 PM

GitHub: 475 stars · 5 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
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 SouravRoy-ETL/slothdb, 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
    Reposition the README's opening paragraph to emphasize core identity and intended scope

    Why:

    CURRENT
    <div align="center"><h3>An experimental embedded SQL engine.</h3><p>SlothDB is a from-scratch C++20 embedded SQL database in active development. Same model as DuckDB and SQLite: query Parquet, CSV, JSON, Arrow, Avro, SQLite, and Excel files directly with SQL, in-process. Early-stage; read the <a href="#status">Status</a> section below before treating any performance numbers as final.</p>
    COPY-PASTE FIX
    <div align="center"><h3>SlothDB: A C++20 Embedded SQL Engine for Multi-Format Analytics</h3><p>SlothDB is a from-scratch C++20 embedded SQL database designed for high-performance, in-process querying of diverse file formats like Parquet, CSV, JSON, Arrow, Avro, SQLite, and Excel. Following the model of DuckDB and SQLite, it aims to provide a robust analytical database solution. While currently in active, experimental development, its core focus is on powerful SQL capabilities for data analysis, not small-scale or prototyping-only use cases.</p>
  • mediumreadme#2
    Reframe the 'Ask in any language. Get SQL.' section as a feature, not primary identity

    Why:

    CURRENT
    ## Ask in any language. Get SQL. Type `.ask` at the `slothdb>` prompt. A rules parser handles catalog questions and common English shapes in under 10 ms with no model. Anything else fall
    COPY-PASTE FIX
    Move this section further down in the README, perhaps after core usage examples, and rename its heading to `## Natural Language to SQL Interface (Experimental Feature)` with an introductory sentence like: "SlothDB includes an experimental natural language interface to assist with SQL queries and catalog exploration."
  • lowreadme#3
    Add a dedicated 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    Add a new section `## Comparison to Alternatives (DuckDB, SQLite, Polars)` and briefly outline SlothDB's unique approach or differentiators.

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 SouravRoy-ETL/slothdb
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
duckdb/duckdb
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. duckdb/duckdb · recommended 2×
  2. pola-rs/polars · recommended 2×
  3. SQLite · recommended 2×
  4. apache/datafusion · recommended 1×
  5. ClickHouse/ClickHouse · recommended 1×
  • CATEGORY QUERY
    Need an embedded SQL engine to query Parquet, CSV, and JSON files directly in-process.
    you: not recommended
    AI recommended (in order):
    1. DuckDB (duckdb/duckdb)
    2. Polars (pola-rs/polars)
    3. SQLite
    4. DataFusion (apache/datafusion)
    5. ClickHouse (ClickHouse/ClickHouse)

    AI recommended 5 alternatives but never named SouravRoy-ETL/slothdb. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an in-process analytical SQL database for various file formats like Arrow or Excel.
    you: not recommended
    AI recommended (in order):
    1. DuckDB (duckdb/duckdb)
    2. SQLite
    3. H2 Database (h2database/h2database)
    4. HSQLDB (hsqldb/hsqldb)
    5. Apache Calcite (apache/calcite)
    6. Polars (pola-rs/polars)

    AI recommended 6 alternatives but never named SouravRoy-ETL/slothdb. 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 SouravRoy-ETL/slothdb?
    pass
    AI named SouravRoy-ETL/slothdb explicitly

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

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

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

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SouravRoy-ETL/slothdb — 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