RRepoGEO

REPOGEO REPORT · LITE

supermemoryai/markdowner

Default branch main · commit f8878349 · scanned 6/28/2026, 9:42:37 AM

GitHub: 1,965 stars · 147 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
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 supermemoryai/markdowner, 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
  • highreadme#1
    Strengthen README's opening sentence to highlight key differentiators

    Why:

    CURRENT
    A fast tool to convert any website into LLM-ready markdown data.
    COPY-PASTE FIX
    A fast, free, and self-hostable tool to convert any website into structured, LLM-ready markdown data, specifically optimized for AI applications.
  • mediumreadme#2
    Clarify differentiation from generic tools in README's 'Why?' section

    Why:

    CURRENT
    The 'Why?' section primarily contrasts with proprietary tools like Jina and Firecrawl.
    COPY-PASTE FIX
    Add the following sentence to the end of the 'Why?' section: "Unlike generic HTML-to-markdown converters, Markdowner is specifically engineered for LLM ingestion, providing structured, clean data optimized for AI applications, and is fully free and self-hostable."

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 supermemoryai/markdowner
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
mozilla/readability
Recommended in 3 of 2 queries
COMPETITOR LEADERBOARD
  1. mozilla/readability · recommended 3×
  2. buriy/python-readability · recommended 2×
  3. jgm/pandoc · recommended 2×
  4. adbar/trafilatura · recommended 2×
  5. Alirun/html2text · recommended 1×
  • CATEGORY QUERY
    How to convert web pages into structured markdown for AI applications?
    you: not recommended
    AI recommended (in order):
    1. Readability.js (mozilla/readability)
    2. python-readability (buriy/python-readability)
    3. html2text (Alirun/html2text)
    4. readability (npm package) (mozilla/readability)
    5. Pandoc (jgm/pandoc)
    6. Turndown (domchristie/turndown)
    7. Trafilatura (adbar/trafilatura)
    8. Beautiful Soup 4 (crummy/BeautifulSoup)
    9. Mercury Web Parser

    AI recommended 9 alternatives but never named supermemoryai/markdowner. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a free, self-hostable tool to extract clean markdown from websites.
    you: not recommended
    AI recommended (in order):
    1. Readability.js (mozilla/readability)
    2. python-readability (buriy/python-readability)
    3. Mercury Parser (postlight/mercury-parser)
    4. Trafilatura (adbar/trafilatura)
    5. Goose3 (goose3/goose3)
    6. Pandoc (jgm/pandoc)
    7. html2text (Alir3z4/html2text)

    AI recommended 7 alternatives but never named supermemoryai/markdowner. 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 supermemoryai/markdowner?
    pass
    AI named supermemoryai/markdowner explicitly

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

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

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

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supermemoryai/markdowner — 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