RRepoGEO

REPOGEO REPORT · LITE

web-infra-dev/rsdoctor

Default branch main · commit 6a7eb2ca · scanned 6/29/2026, 12:01:46 PM

GitHub: 1,136 stars · 97 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 web-infra-dev/rsdoctor, 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
    Strengthen README opening to emphasize build performance optimization

    Why:

    CURRENT
    Rsdoctor is a build analyzer tailored for the Rspack ecosystem and fully compatible with the webpack ecosystem. Rsdoctor is committed to being a one-stop, intelligent build analyzer that makes the build process transparent, predictable, and optimizable through visualization and smart analysis, helping development teams precisely identify bottlenecks, optimize performance, and improve engineering quality.
    COPY-PASTE FIX
    Rsdoctor is a one-stop, intelligent build analyzer designed to diagnose and optimize slow JavaScript build times and large bundle sizes for Rspack and webpack projects. It makes the build process transparent, predictable, and optimizable through visualization and smart analysis, helping development teams precisely identify bottlenecks, optimize performance, and improve engineering quality.
  • mediumtopics#2
    Add specific performance and optimization topics

    Why:

    CURRENT
    analyze, build-analyzer, bundle, hacktoberfest, rspack, rstack, webpack
    COPY-PASTE FIX
    analyze, build-analyzer, bundle, hacktoberfest, rspack, rstack, webpack, performance, optimization, diagnostics, build-performance
  • mediumreadme#3
    Add a comparison section to differentiate from competitors

    Why:

    COPY-PASTE FIX
    ## 💡 Why Rsdoctor? (Compared to X, Y, Z)

While tools like Webpack Bundle Analyzer focus primarily on visualizing bundle size, Rsdoctor provides a deeper, one-stop analysis of the entire build process. It offers detailed insights into compilation behavior, build-time analysis (Loader, Plugin, Resolver), and anti-degradation capabilities, making the complex build process transparent and optimizable beyond just artifact size.

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 web-infra-dev/rsdoctor
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
webpack-contrib/webpack-bundle-analyzer
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. webpack-contrib/webpack-bundle-analyzer · recommended 1×
  2. pmmmwh/speedy-webpack-plugin · recommended 1×
  3. eslint/eslint · recommended 1×
  4. import-js/eslint-plugin-import · recommended 1×
  5. danvk/source-map-explorer · recommended 1×
  • CATEGORY QUERY
    How to diagnose slow JavaScript build times and optimize project compilation performance?
    you: not recommended
    AI recommended (in order):
    1. Webpack Bundle Analyzer (webpack-contrib/webpack-bundle-analyzer)
    2. Speedy Webpack Plugin (pmmmwh/speedy-webpack-plugin)
    3. ESLint (eslint/eslint)
    4. eslint-plugin-import (import-js/eslint-plugin-import)
    5. Source Map Explorer (danvk/source-map-explorer)
    6. Turborepo (vercel/turborepo)
    7. Nx (nrwl/nx)
    8. SWC (swc-project/swc)
    9. esbuild (evanw/esbuild)
    10. Babel (babel/babel)
    11. Webpack (webpack/webpack)
    12. Chrome DevTools

    AI recommended 12 alternatives but never named web-infra-dev/rsdoctor. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a tool to visualize module bundler compilation behavior and identify performance issues.
    you: not recommended
    AI recommended (in order):
    1. Webpack Bundle Analyzer
    2. Source Map Explorer
    3. Rollup Visualizer
    4. Parcel Analyzer
    5. Vite Visualizer
    6. BundlePhobia
    7. Lighthouse

    AI recommended 7 alternatives but never named web-infra-dev/rsdoctor. 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 web-infra-dev/rsdoctor?
    pass
    AI named web-infra-dev/rsdoctor explicitly

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

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

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

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  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite