RRepoGEO

REPOGEO REPORT · LITE

shibing624/pycorrector

Default branch master · commit 7e3caeaf · scanned 5/16/2026, 10:26:57 AM

GitHub: 6,443 stars · 1,161 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 shibing624/pycorrector, 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 README H1 to emphasize specialized Chinese error correction

    Why:

    CURRENT
    # pycorrector: useful python text correction toolkit
    COPY-PASTE FIX
    # pycorrector: Advanced Chinese Text Error Correction Toolkit (文本纠错)
  • mediumreadme#2
    Add a clear differentiator statement to the README introduction

    Why:

    COPY-PASTE FIX
    Unlike general Chinese NLP toolkits, pycorrector is singularly focused on comprehensive text error correction, leveraging state-of-the-art models like Kenlm, T5, MacBERT, ChatGLM3, and Qwen2.5 specifically for Chinese phonetic, shape, and grammatical errors.
  • lowcomparison#3
    Create a dedicated 'Comparison' section in the README

    Why:

    COPY-PASTE FIX
    Add a new section `## Comparison` or `## Why pycorrector?` that briefly explains how `pycorrector`'s specialized focus on error correction differs from general-purpose Chinese NLP libraries.

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 shibing624/pycorrector
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
jxmorris12/languagetool-python
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. jxmorris12/languagetool-python · recommended 1×
  2. FudanNLP/FudanNLP · recommended 1×
  3. hankcs/HanLP · recommended 1×
  4. fxsjy/jieba · recommended 1×
  5. HIT-SCIR/pyltp · recommended 1×
  • CATEGORY QUERY
    What are the best Python libraries for correcting grammatical and spelling errors in Chinese text?
    you: not recommended
    AI recommended (in order):
    1. languagetool-python (jxmorris12/languagetool-python)
    2. FudanNLP (FudanNLP/FudanNLP)
    3. HanLP (hankcs/HanLP)
    4. Jieba (fxsjy/jieba)
    5. Pyltp (HIT-SCIR/pyltp)

    AI recommended 5 alternatives but never named shibing624/pycorrector. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I automatically detect and correct common phonetic and shape-based errors in Chinese text?
    you: not recommended
    AI recommended (in order):
    1. Baidu NLP
    2. PaddleNLP
    3. ERNIE
    4. Tencent Cloud NLP
    5. HanLP
    6. Jieba
    7. Pypinyin
    8. PyTorch
    9. TensorFlow

    AI recommended 9 alternatives but never named shibing624/pycorrector. 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 shibing624/pycorrector?
    pass
    AI did not name shibing624/pycorrector — 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 shibing624/pycorrector in production, what risks or prerequisites should they evaluate first?
    pass
    AI named shibing624/pycorrector 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 shibing624/pycorrector solve, and who is the primary audience?
    pass
    AI named shibing624/pycorrector explicitly

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

Embed your GEO score

Drop this badge into the README of shibing624/pycorrector. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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shibing624/pycorrector — 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