RRepoGEO

REPOGEO REPORT · LITE

midday-ai/packrun

Default branch main · commit fe5a8c49 · scanned 5/27/2026, 3:42:36 AM

GitHub: 3,843 stars · 410 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 midday-ai/packrun, 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
  • highabout#1
    Update the repository description to be more explicit

    Why:

    CURRENT
    npm for agents and humans
    COPY-PASTE FIX
    A real-time npm registry and package comparison engine specifically designed for AI agents and developers, offering metrics like bundle size, freshness, and community score.
  • highlicense#2
    Add a LICENSE file to the repository root

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Add a LICENSE file (e.g., MIT, Apache-2.0, GPL-3.0) to the repository root.
  • mediumtopics#3
    Update repository topics to reflect purpose and audience

    Why:

    CURRENT
    monorepo, nextjs, shadcn, tailwind, turborepo
    COPY-PASTE FIX
    npm, package-manager, ai-agents, package-comparison, real-time-metrics, developer-tools, coding-assistant, mcp-server

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 midday-ai/packrun
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
BundlePhobia
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. BundlePhobia · recommended 1×
  2. npm trends · recommended 1×
  3. Package Phobia · recommended 1×
  4. Snyk Advisor · recommended 1×
  5. npm view / yarn info · recommended 1×
  • CATEGORY QUERY
    What's the best way to compare npm packages by metrics like bundle size and freshness?
    you: not recommended
    AI recommended (in order):
    1. BundlePhobia
    2. npm trends
    3. Package Phobia
    4. Snyk Advisor
    5. npm view / yarn info
    6. webpack-bundle-analyzer

    AI recommended 6 alternatives but never named midday-ai/packrun. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can AI coding assistants intelligently recommend optimal packages based on real-time data?
    you: not recommended
    AI recommended (in order):
    1. GitHub
    2. PyPI
    3. npm
    4. Maven Central
    5. Libraries.io
    6. Datadog
    7. New Relic
    8. Prometheus
    9. Grafana
    10. Sentry
    11. Snyk
    12. Dependabot
    13. OWASP Dependency-Check
    14. WhiteSource Bolt
    15. GitHub Copilot
    16. Tabnine
    17. IntelliJ IDEA
    18. VS Code
    19. FOSSA
    20. Black Duck by Synopsys

    AI recommended 20 alternatives but never named midday-ai/packrun. 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 midday-ai/packrun?
    pass
    AI named midday-ai/packrun explicitly

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

  • If a team adopts midday-ai/packrun in production, what risks or prerequisites should they evaluate first?
    pass
    AI named midday-ai/packrun 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 midday-ai/packrun solve, and who is the primary audience?
    pass
    AI named midday-ai/packrun 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 midday-ai/packrun. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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  • Brand-free category queries5 vs 2 in Lite
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