RRepoGEO

REPOGEO REPORT · LITE

afc163/fanyi

Default branch main · commit 53a0c33c · scanned 5/26/2026, 3:48:06 AM

GitHub: 1,542 stars · 144 forks

AI VISIBILITY SCORE
27 /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
1 / 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 afc163/fanyi, 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 Node.js and LLM

    Why:

    CURRENT
    A 🇨🇳 and 🇺🇸🇬🇧 translator in your command line, powered by iciba and deepseek.
    COPY-PASTE FIX
    A fast, Node.js-powered 🇨🇳 and 🇺🇸🇬🇧 command-line translator, leveraging large language models (Deepseek) and iciba for accurate results.
  • mediumtopics#2
    Add general LLM topics

    Why:

    CURRENT
    chinese, command-line, command-line-tools, groq, llama3, nodejs, translation, translator
    COPY-PASTE FIX
    chinese, command-line, command-line-tools, groq, llama3, llm, large-language-models, nodejs, translation, translator
  • lowabout#3
    Enhance description to highlight LLM integration

    Why:

    CURRENT
    A 🇨🇳 and 🇺🇸 translator in your command line
    COPY-PASTE FIX
    A fast command-line translator for 🇨🇳 and 🇺🇸, powered by large language models (Deepseek) and iciba.

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 afc163/fanyi
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
translate-shell
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. translate-shell · recommended 1×
  2. gtranslate-cli · recommended 1×
  3. trans-cli · recommended 1×
  4. curl · recommended 1×
  5. google-translate-api-x · recommended 1×
  • CATEGORY QUERY
    How can I quickly translate Chinese to English directly from my terminal?
    you: not recommended
    AI recommended (in order):
    1. translate-shell
    2. gtranslate-cli
    3. trans-cli
    4. curl

    AI recommended 4 alternatives but never named afc163/fanyi. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a command-line translation tool powered by large language models for Node.js.
    you: not recommended
    AI recommended (in order):
    1. google-translate-api-x
    2. openai
    3. deepl-node
    4. azure-ai-text-translation
    5. cld

    AI recommended 5 alternatives but never named afc163/fanyi. 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 afc163/fanyi?
    pass
    AI did not name afc163/fanyi — 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 afc163/fanyi in production, what risks or prerequisites should they evaluate first?
    pass
    AI named afc163/fanyi 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 afc163/fanyi solve, and who is the primary audience?
    pass
    AI did not name afc163/fanyi — 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?

Embed your GEO score

Drop this badge into the README of afc163/fanyi. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/afc163/fanyi.svg)](https://repogeo.com/en/r/afc163/fanyi)
HTML
<a href="https://repogeo.com/en/r/afc163/fanyi"><img src="https://repogeo.com/badge/afc163/fanyi.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

afc163/fanyi — 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
afc163/fanyi — RepoGEO report