RRepoGEO

REPOGEO REPORT · LITE

chonkie-inc/chonkie

Default branch main · commit 5bec52bf · scanned 6/27/2026, 3:36:44 AM

GitHub: 4,183 stars · 280 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
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 chonkie-inc/chonkie, 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
    Clarify project identity in README's opening statement

    Why:

    CURRENT
    _The lightweight ingestion library for fast, efficient and robust RAG pipelines_
    COPY-PASTE FIX
    Chonkie is a lightweight Python library for fast, efficient, and robust RAG pipelines.
  • mediumreadme#2
    Add a prominent 'What is Chonkie?' section

    Why:

    COPY-PASTE FIX
    Add a new H2 section, e.g., `## What is Chonkie?`, followed by a paragraph expanding on its core purpose, target users, and key benefits for RAG systems.
  • lowcomparison#3
    Create a 'Comparison with Alternatives' section

    Why:

    COPY-PASTE FIX
    Add a new H2 section, e.g., `## Comparison with Alternatives`, detailing how Chonkie differentiates itself from popular tools like LangChain and LlamaIndex, emphasizing its lightweight nature, speed, and specific focus on ingestion.

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 chonkie-inc/chonkie
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. NLTK · recommended 2×
  4. spaCy · recommended 1×
  5. Haystack · recommended 1×
  • CATEGORY QUERY
    What are some fast and efficient text splitting libraries for building robust RAG systems?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. NLTK
    4. spaCy
    5. Haystack
    6. RecursiveCharacterTextSplitter

    AI recommended 6 alternatives but never named chonkie-inc/chonkie. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a lightweight ingestion library for text chunking and embedding in AI applications.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Sentence Transformers
    4. Hugging Face `transformers` library
    5. `tokenizers`
    6. NLTK
    7. SpaCy

    AI recommended 7 alternatives but never named chonkie-inc/chonkie. 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 chonkie-inc/chonkie?
    pass
    AI named chonkie-inc/chonkie explicitly

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

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

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

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chonkie-inc/chonkie — 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