RRepoGEO

REPOGEO REPORT · LITE

bird-bench/BIRD-Interact

Default branch main · commit 451fe2c3 · scanned 6/25/2026, 3:23:06 PM

GitHub: 1,006 stars · 21 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 bird-bench/BIRD-Interact, 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
  • hightopics#1
    Add relevant topics for better categorization

    Why:

    COPY-PASTE FIX
    text-to-sql, nlp, benchmark, evaluation, interactive-ai, multi-turn, llm, database
  • highreadme#2
    Reposition README's opening to highlight interactive evaluation

    Why:

    COPY-PASTE FIX
    BIRD-INTERACT is a novel benchmark for Text-to-SQL evaluation, uniquely focusing on dynamic, multi-turn interactions where models must interpret user feedback and refine queries. This re-imagines how we assess the accuracy and robustness of interactive Text-to-SQL systems.
  • mediumreadme#3
    Add a brief comparison section to key alternatives

    Why:

    COPY-PASTE FIX
    ## Comparison with Other Text-to-SQL Benchmarks

While benchmarks like Spider-Syn and SParC are foundational for single-turn or basic multi-turn Text-to-SQL, BIRD-INTERACT distinguishes itself by evaluating the complexities of dynamic, interactive conversations, where user feedback and iterative query refinement are central.

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 bird-bench/BIRD-Interact
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Spider-Syn
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Spider-Syn · recommended 1×
  2. SParC · recommended 1×
  • CATEGORY QUERY
    How to rigorously evaluate the accuracy and robustness of Text-to-SQL models?
    you: not recommended
    Show full AI answer
  • CATEGORY QUERY
    Seeking advanced benchmarks for interactive and dynamic Text-to-SQL query generation systems.
    you: not recommended
    AI recommended (in order):
    1. Spider-Syn
    2. SParC

    AI recommended 2 alternatives but never named bird-bench/BIRD-Interact. 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 bird-bench/BIRD-Interact?
    pass
    AI named bird-bench/BIRD-Interact explicitly

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

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

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

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bird-bench/BIRD-Interact — 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