RRepoGEO

REPOGEO REPORT · LITE

dathere/qsv

Default branch master · commit 60ad316e · scanned 5/26/2026, 8:12:33 PM

GitHub: 3,652 stars · 104 forks

AI VISIBILITY SCORE
33 /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
2 / 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 dathere/qsv, 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 H1 to specify tabular data and command-line focus

    Why:

    CURRENT
    ## qsv: Blazing-fast Data-Wrangling toolkit
    COPY-PASTE FIX
    ## qsv: Blazing-fast Command-Line Toolkit for Tabular Data Wrangling (CSV, Excel, Parquet)
  • mediumreadme#2
    Add an explicit statement about qsv's Rust-based performance differentiator

    Why:

    COPY-PASTE FIX
    Built in Rust, `qsv` offers significantly faster execution and lower memory consumption compared to Python-based alternatives like `csvkit` for large datasets.
  • lowcomparison#3
    Create a dedicated comparison section in the README

    Why:

    COPY-PASTE FIX
    Add a new section, e.g., `## Comparison with other tools`, explicitly comparing `qsv` to tools like `csvkit`, `DuckDB CLI`, `Polars CLI`, `jq`, `awk`, and `miller` for tabular data tasks, highlighting `qsv`'s strengths.

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 dathere/qsv
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
jq
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. jq · recommended 1×
  2. awk · recommended 1×
  3. sed · recommended 1×
  4. miller · recommended 1×
  5. datamash · recommended 1×
  • CATEGORY QUERY
    Need a high-performance command-line utility for fast data wrangling and transformation tasks.
    you: not recommended
    AI recommended (in order):
    1. jq
    2. awk
    3. sed
    4. miller
    5. datamash
    6. q
    7. ripgrep

    AI recommended 7 alternatives but never named dathere/qsv. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good command-line tools for SQL-like queries on CSV and Parquet files?
    you: not recommended
    AI recommended (in order):
    1. DuckDB CLI (duckdb/duckdb)
    2. Polars CLI (pola-rs/polars)
    3. q (harelba/q)
    4. TextQL (dinedal/textql)
    5. sqlite-utils (simonw/sqlite-utils)
    6. csvkit (wireservice/csvkit)

    AI recommended 6 alternatives but never named dathere/qsv. 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 dathere/qsv?
    pass
    AI did not name dathere/qsv — likely talking about a different project

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

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

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

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dathere/qsv — 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