RRepoGEO

REPOGEO REPORT · LITE

mangiucugna/json_repair

Default branch main · commit d7f2a3bd · scanned 5/24/2026, 8:51:28 PM

GitHub: 4,918 stars · 197 forks

AI VISIBILITY SCORE
67 /100
Needs work
Category recall
1 / 2
Avg rank #1.0 when recommended
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 mangiucugna/json_repair, 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
    Add a 'Why json_repair for LLM/API output?' section to the README

    Why:

    COPY-PASTE FIX
    Create a new section, perhaps titled 'Why json_repair for LLM/API Output?' or 'Key Differentiators', that explicitly explains its robust, state machine-based approach and how it specifically addresses the common issues with malformed JSON from LLMs and APIs, contrasting it with simpler or generic parsing methods.
  • mediumreadme#2
    Expand the 'Motivation' section in the README

    Why:

    CURRENT
    Some LLMs are a bit iffy when it comes to
    COPY-PASTE FIX
    Some LLMs are a bit iffy when it comes to consistently generating perfectly valid JSON. This library provides a robust solution to automatically correct common errors, ensuring reliable structured data extraction from their responses.
  • lowreadme#3
    Clarify the 'Audio overview' in the Demo section

    Why:

    CURRENT
    Audio overview: NotebookLM introduction
    COPY-PASTE FIX
    Audio overview: [Link to NotebookLM introduction] (a brief explanation of what the audio covers)

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
1 / 2
50% of queries surface mangiucugna/json_repair
Avg rank
#1.0
Lower is better. #1 = top recommendation.
Share of voice
8%
Of all named tools, what % are you?
Top rival
json5
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. json5 · recommended 2×
  2. json module · recommended 1×
  3. demjson3 · recommended 1×
  4. ast.literal_eval · recommended 1×
  5. eval() · recommended 1×
  • CATEGORY QUERY
    How to fix malformed JSON output from LLMs or API responses in Python?
    you: not recommended
    AI recommended (in order):
    1. json5
    2. json module
    3. demjson3
    4. ast.literal_eval
    5. eval()
    6. tenacity

    AI recommended 6 alternatives but never named mangiucugna/json_repair. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Python library to automatically repair JSON with missing quotes, commas, or truncated values?
    you: #1
    AI recommended (in order):
    1. json_repair ← you
    2. demjson
    3. json5
    4. orjson
    5. hjson
    6. pyjson5
    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 mangiucugna/json_repair?
    pass
    AI did not name mangiucugna/json_repair — 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 mangiucugna/json_repair in production, what risks or prerequisites should they evaluate first?
    pass
    AI named mangiucugna/json_repair 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 mangiucugna/json_repair solve, and who is the primary audience?
    pass
    AI named mangiucugna/json_repair explicitly

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

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MARKDOWN (README)
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  • Brand-free category queries5 vs 2 in Lite
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