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burakaydinofficial

searxng-deepdive

web_url_read

Fetch a URL and get clean Markdown content. Use after search to read page text, with options to extract headings, sections, or paragraphs for token-efficient reading.

Instructions

Fetch a URL and convert its HTML content to clean Markdown.

Use after search (or its variants) when you have a URL and want the actual page text, not just the search snippet. Lightweight HTTP + HTML→Markdown — handles ~80% of the static-HTML web (Wikipedia, docs sites, blogs, news, GitHub READMEs).

What this DOES NOT handle: • JavaScript-rendered pages (React/Vue/Angular SPAs) — content loads after the initial HTML, which we don't execute. Returns minimal or empty markdown for these. • Bot-protected pages (Cloudflare challenge, captcha) — typically fail with HTTP 403/503. • Binary resources (PDF, images, archives) — returns an explanatory hint instead of garbled bytes.

For those cases, fall back to a Chromium-backed reader (e.g. Crawl4AI exposed via the SearXNG-Compose reader profile).

Token-efficient extraction modes (priority order — first one set wins): • readHeadings:true — returns ONLY the heading list (hierarchical TOC). Cheapest survey of a long page. • section:'' — returns content under first matching heading, up to the next same-or-higher heading. Use after readHeadings to jump. • paragraphRange:'3-7' — 1-indexed paragraph slice; supports 'N' (single) or 'N-M' (range). • startChar + maxLength — character window pagination. Response includes total_length and truncated so you can plan follow-up calls.

If no extraction mode is set, returns the full Markdown.

Recommended workflow for long pages:

  1. web_url_read(url, readHeadings: true) ← TOC scan

  2. web_url_read(url, section: '') ← targeted read Far more token-efficient than fetching the full page up front.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesHTTP(S) URL to fetch and convert to Markdown. Static pages only — for JavaScript-rendered SPAs and bot-protected sites, use a Chromium-backed reader instead.
sectionNoSubstring match against headings (case-insensitive). Returns content under the FIRST heading containing this text, up to the next heading at the same or higher level. Use after readHeadings to read a targeted section without dumping the whole page.
maxLengthNoMaximum characters to return. Use with startChar for paginated reading; the response includes `total_length` and `truncated` so you can plan follow-up calls.
startCharNoCharacter offset where extraction begins. Default 0.
readHeadingsNoWhen true, returns ONLY the page's heading list as a hierarchical TOC (token-cheap survey). Pair with a follow-up call using `section` to read the chunk you actually want.
paragraphRangeNo1-indexed paragraph range, syntax 'N' or 'N-M' (e.g. '3-7' for paragraphs 3–7, '5' for paragraph 5 alone). Useful for sequential reading of long pages without re-fetching.
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, description fully covers behavior: limitations (JS-rendered, bot-protected, binary), response fields (total_length, truncated), and extraction mode priority. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with bullet points and sections. Slightly long but every sentence adds value. Front-loaded with purpose and use cases.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema, description adequately explains response fields (total_length, truncated). Covers all 6 parameters, usage patterns, and limitations. Complete for a complex tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, providing baseline of 3. The description adds value by explaining priority order, use of section matching, and workflow integration, going beyond schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it fetches a URL and converts HTML to Markdown. It distinguishes from sibling tools like search by specifying it provides actual page text, not snippets. Explicitly lists what it does and does not handle.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit context for use: 'Use after search' and suggests fallback to Chromium-based reader for problematic pages. Details priority order for extraction modes and a recommended workflow for long pages.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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