RRepoGEO

REPOGEO REPORT · LITE

samchon/typia

Default branch master · commit 1dc6f4b9 · scanned 6/19/2026, 11:06:57 AM

GitHub: 5,834 stars · 225 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)

2 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 samchon/typia, 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 concise introductory paragraph to the README

    Why:

    CURRENT
    The README currently starts with # Typia followed by badges and code examples.
    COPY-PASTE FIX
    Typia is a super-fast TypeScript library for runtime type validation, serialization, and JSON schema generation. It uniquely leverages compile-time transformations to generate highly optimized code directly from your existing TypeScript types, eliminating redundant schema definitions and ensuring peak performance for tasks like data validation, API serialization, and LLM function calling.
  • mediumtopics#2
    Add high-signal topics reinforcing compile-time and core functionalities

    Why:

    CURRENT
    agentic-ai, ajv, checker, fast, generator, hacktoberfest, json, json-schema, llm-function-calling, openapi, protobuf, random, runtime, stringify, transform, type, typescript, validator
    COPY-PASTE FIX
    Add `compile-time-validation`, `typescript-transformer`, `data-validation`, `data-serialization`, `type-safe-json` to the existing topics.
  • lowcomparison#3
    Add a 'Why Typia?' or 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, such as 'Why Typia?' or 'Comparison with Alternatives,' that clearly articulates Typia's compile-time advantage and how it differs from schema-first or runtime-only validation libraries like Zod, Valibot, or Yup.

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 samchon/typia
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Zod
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Zod · recommended 1×
  2. Valibot · recommended 1×
  3. Yup · recommended 1×
  4. TypeBox · recommended 1×
  5. io-ts · recommended 1×
  • CATEGORY QUERY
    Need a performant TypeScript library for runtime type validation and data serialization.
    you: not recommended
    AI recommended (in order):
    1. Zod
    2. Valibot
    3. Yup
    4. TypeBox
    5. io-ts

    AI recommended 5 alternatives but never named samchon/typia. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a tool to generate JSON schemas and validate LLM structured outputs.
    you: not recommended
    AI recommended (in order):
    1. Pydantic
    2. JSON Schema Faker
    3. jsonschema
    4. OpenAPI Generator
    5. Quicktype
    6. JSON Schema Store
    7. VS Code
    8. YAML and JSON Schema extension
    9. JSON Schema Editor

    AI recommended 9 alternatives but never named samchon/typia. 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 samchon/typia?
    pass
    AI named samchon/typia explicitly

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

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

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

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samchon/typia — 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