RRepoGEO

REPOGEO REPORT · LITE

Snailclimb/interview-guide

Default branch master · commit af0dcc25 · scanned 5/17/2026, 8:53:24 PM

GitHub: 2,117 stars · 468 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
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 Snailclimb/interview-guide, 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 clear, concise English summary at the top of the README.

    Why:

    COPY-PASTE FIX
    An open-source AI platform for intelligent resume analysis, AI mock interviews, and RAG knowledge base, built with Spring Boot and Spring AI.
  • hightopics#2
    Add application-domain-specific topics.

    Why:

    CURRENT
    gradle, itext7, mapstruct, pgvector, postgresql, rag, redis, redisson, redisstreams, rustfs, springai, springboot, springboot4, tika
    COPY-PASTE FIX
    ai-interviewer, resume-analysis, mock-interview, rag-application, llm-application, java-application, spring-ai, pgvector, postgresql, redis, springboot, gradle, itext7, mapstruct, redisson, redisstreams, rustfs, tika
  • mediumabout#3
    Rephrase the description to be more direct about it being an AI application.

    Why:

    CURRENT
    基于 Spring Boot 4.0 + Java 21 + Spring AI + PostgreSQL + pgvector + RustFS + Redis，实现简历智能分析、AI模拟面试、知识库RAG检索等核心功能。非常适合作为学习和简历项目，学习门槛低。
    COPY-PASTE FIX
    An open-source AI platform built with Spring Boot 4.0, Java 21, Spring AI, PostgreSQL (pgvector), RustFS, and Redis. It provides intelligent resume analysis, AI mock interviews, and RAG knowledge base retrieval. Ideal for learning and portfolio projects.

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 Snailclimb/interview-guide
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Transformers
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 1×
  2. spaCy · recommended 1×
  3. OpenAI API · recommended 1×
  4. Google Cloud Speech-to-Text · recommended 1×
  5. Azure Speech-to-Text · recommended 1×
  • CATEGORY QUERY
    How can I build an AI platform for resume analysis and mock interviews?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. spaCy
    3. OpenAI API
    4. Google Cloud Speech-to-Text
    5. Azure Speech-to-Text
    6. PyTorch
    7. TensorFlow
    8. Scikit-learn
    9. Streamlit
    10. Gradio

    AI recommended 10 alternatives but never named Snailclimb/interview-guide. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking open-source Java projects demonstrating RAG with Spring AI and pgvector.
    you: not recommended
    AI recommended (in order):
    1. Spring AI Samples
    2. Spring AI Reference Application
    3. Chroma
    4. Milvus
    5. Pinecone
    6. Weaviate

    AI recommended 6 alternatives but never named Snailclimb/interview-guide. 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 Snailclimb/interview-guide?
    pass
    AI did not name Snailclimb/interview-guide — 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 Snailclimb/interview-guide in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Snailclimb/interview-guide 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 Snailclimb/interview-guide solve, and who is the primary audience?
    pass
    AI did not name Snailclimb/interview-guide — 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 Snailclimb/interview-guide. 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/Snailclimb/interview-guide.svg)](https://repogeo.com/en/r/Snailclimb/interview-guide)
HTML
<a href="https://repogeo.com/en/r/Snailclimb/interview-guide"><img src="https://repogeo.com/badge/Snailclimb/interview-guide.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

Snailclimb/interview-guide — 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