Tool A

HTML to Markdown for AI

Paste HTML or fetch a public page, strip layout clutter on the server, and export a tighter Markdown payload for prompts, RAG, and automation.

Built for prompt-budget triageServer-side URL cleanup to avoid CORS painMarkdown, token savings, and `llms.txt` export

Input

Convert web content for AI

Server-side cleanup path

HTML input

Best for raw scraper output, copied page source, or CMS fragments that still carry layout markup.

Keeps semantic content like headings, lists, and tables while stripping scripts, nav, footers, and decorative SVG markup.

Output

Ready for your prompt or pipeline

Result panel

Lean Markdown lands here.

Run a conversion to preview the cleaned output, inspect the size reduction, and export the content in one click.

Implementation notes

Designed for retrieval, prompting, and quick human QA.

This first PromptStage tool favors reliability over bells and whistles. The converter runs on the server so the same cleanup path can handle both pasted HTML and remote URLs while enforcing fetch limits safely.

Why this helps AI workflows

Raw pages carry navigation, trackers, wrappers, and decorative markup that waste prompt space without adding meaning.

What gets preserved

The converter keeps headings, paragraphs, lists, tables, code blocks, and the main content body while normalizing useful links.

What gets stripped

Scripts, styles, nav chrome, cookie overlays, sidebars, forms, footers, and hidden layout modules are removed before Markdown generation.

FAQ

Built for agent inputs, not generic site export.

The goal is a cleaner prompt payload and a tighter context window, not a publishing workflow or browser-rendered scraper.

What kinds of pages work best?

Docs pages, blog posts, changelogs, help-center articles, and most public knowledge-base pages work well when the useful content already exists in the returned HTML.

Does it render client-side apps?

No. The tool fetches public HTML on the server and converts what is already present in the response. It does not execute browser-side app code or bypass logins.

What is the output meant for?

The output is designed for prompt inputs, retrieval pipelines, agent workflows, and quick human QA where semantic signal density matters more than pixel-perfect reproduction.