RRepoGEO

REPOGEO REPORT · LITE

Feather-2/Burner-X

Default branch main · commit c9e6410c · scanned 5/16/2026, 4:08:36 AM

GitHub: 1,692 stars · 661 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 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 Feather-2/Burner-X, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Update the repository description for clarity and disambiguation

    Why:

    CURRENT
    Burner X - 浏览器即开即用，AI文献识别、文档批量翻译、阅读与智能分析工具 丨BYOK
    COPY-PASTE FIX
    Paper Burner X: 浏览器即开即用的AI文献识别、文档批量翻译、阅读与智能分析工具。本地优先，BYOK。
  • mediumreadme#2
    Add a comparison section to the README

    Why:

    COPY-PASTE FIX
    Add a new section, e.g., `## 💡 与其他工具对比 (Comparison with other tools)`, that explicitly highlights how Paper Burner X differs from generic translation tools (DeepL, Google Translate), general AI assistants (ChatGPT), and local LLM deployment tools (LocalGPT, Ollama) by focusing on its integrated, browser-based, local-first, research paper specific analysis with format preservation and agentic RAG capabilities.

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 Feather-2/Burner-X
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DeepL Pro
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. DeepL Pro · recommended 1×
  2. Google Translate · recommended 1×
  3. Google Docs · recommended 1×
  4. ChatGPT · recommended 1×
  5. GPT-4 · recommended 1×
  • CATEGORY QUERY
    What are the best AI tools for translating and analyzing research papers with complex formulas?
    you: not recommended
    AI recommended (in order):
    1. DeepL Pro
    2. Google Translate
    3. Google Docs
    4. ChatGPT
    5. GPT-4
    6. Mathpix Snipping Tool
    7. Wolfram Alpha
    8. Trinka AI
    9. Grammarly Business

    AI recommended 9 alternatives but never named Feather-2/Burner-X. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a browser-based AI tool to analyze research documents and extract information locally.
    you: not recommended
    AI recommended (in order):
    1. LocalGPT
    2. PrivateGPT
    3. AnythingLLM
    4. Ollama
    5. GPT4All
    6. LlamaIndex
    7. LangChain

    AI recommended 7 alternatives but never named Feather-2/Burner-X. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • 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 Feather-2/Burner-X?
    pass
    AI named Feather-2/Burner-X explicitly

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

  • If a team adopts Feather-2/Burner-X in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Feather-2/Burner-X 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 Feather-2/Burner-X solve, and who is the primary audience?
    pass
    AI named Feather-2/Burner-X 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 Feather-2/Burner-X. 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/Feather-2/Burner-X.svg)](https://repogeo.com/en/r/Feather-2/Burner-X)
HTML
<a href="https://repogeo.com/en/r/Feather-2/Burner-X"><img src="https://repogeo.com/badge/Feather-2/Burner-X.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

Feather-2/Burner-X — 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