/WikiCleanerWikiCleaner
Clean Wikipedia for humans and machines.
wikicleaner.com ↗
"Our team copies from Wikipedia constantly — for research reports, training data, knowledge bases. Every single time it's the same cleanup: strip the [47][48] citation brackets, remove edit links, fix broken table formatting, delete the navigation junk. We tried browser extensions. We tried writing scrapers that broke every time Wikipedia changed their HTML. We just needed something stupidly simple: paste a URL, get clean text."
Paste Wikipedia into an LLM and you waste thousands of tokens on citation noise, edit links, hidden metadata, and markup that adds zero informational value
Researchers and content teams were spending hours per day on manual formatting cleanup — a problem so mundane nobody had bothered to solve it properly
Developers building RAG pipelines wrote custom scrapers that broke on every Wikipedia HTML change — fragile infrastructure for a critical data source
Burnwire scoped the product to its most essential form: URL in, clean files out. But we went further than basic HTML stripping — we built an LLM-ready output format with prompt injection scanning, designed the tool in Wikipedia's own visual language for instant trust, and made the architecture ephemeral by design: no accounts, no stored content, 10-minute expiry.
Clean HTML (styled, images preserved), Markdown (universal), LLM-ready Markdown (stripped for AI with injection protection), Printable (browser-native save-as-PDF), and RTF (Word-compatible). Every downstream use case covered.
Not just tag stripping. Removes all decorative attributes, scans for prompt injection patterns ('ignore previous instructions'), and adds a safety preface telling the model this is reference content. Built for the AI era.
Killed a Puppeteer PDF dependency that caused 60-second timeouts on long articles. Replaced with browser-native printing — same article, under one second. Eliminated a massive server dependency in the process.
Built an unlisted /llm endpoint that converts any web page — not just Wikipedia — into LLM-ready Markdown. SSRF protection, script/ad stripping, semantic-only output. Positions WikiCleaner as AI content infrastructure, not just a utility.
What we shipped
Problems WikiCleaner solves
Turns any Wikipedia article into LLM-ready content with prompt injection protection — saving thousands of tokens per article
Gives researchers and students clean exports (Markdown, RTF, HTML) without manual formatting cleanup
Provides AI/ML engineers building RAG pipelines with a reliable, structured Wikipedia content source
Hidden /llm tool converts any web page into AI-safe Markdown — positioning WikiCleaner as infrastructure for AI content preparation
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