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AIMLPM

AIMLPM/markcrawl

crawl_site

Extract website content into clean Markdown or text files by crawling pages and removing navigation, scripts, and boilerplate. Build searchable archives for research and data analysis.

Instructions

Crawl a website and save extracted content as clean Markdown or plain text.

This tool fetches pages from the given URL, strips navigation, footers,
scripts, and boilerplate, then saves each page as a Markdown file with a
JSONL index (pages.jsonl). It respects robots.txt and uses sitemap-first
discovery when available.

Use this tool when asked to research, read, analyze, or archive a website.
The output_dir from this tool is required by search_pages, read_page,
list_pages, and extract_data.

Typical workflow: crawl_site → list_pages or search_pages → read_page.

Args:
    url: The base URL to crawl (e.g. "https://docs.example.com/"). Only
        public, non-authenticated pages will be fetched.
    output_dir: Directory to save output files. Each crawl creates .md files
        and a pages.jsonl index here. Default: ./crawl_output
    format: Output format — "markdown" (preserves headings, code blocks,
        lists) or "text" (plain text). Default: "markdown".
    max_pages: Maximum number of pages to save. Set to 0 for unlimited.
        Default: 100. Use lower values (10-20) for quick previews.
    include_subdomains: If True, also crawl subdomains (e.g. docs.example.com
        when crawling example.com). Default: False.
    render_js: If True, use a headless Chromium browser to render JavaScript
        before extracting content. Required for React/Vue/Angular sites.
        Slower but necessary for SPAs. Default: False.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
output_dirNo./crawl_output
formatNomarkdown
max_pagesNo
include_subdomainsNo
render_jsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: robots.txt compliance, sitemap-first discovery, headless Chromium option for SPAs (with performance warning 'Slower but necessary'), and authentication constraints ('Only public, non-authenticated pages will be fetched'). Minor gap: does not mention rate limiting or error handling behavior.

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 logical flow: purpose → usage context → dependencies → workflow → parameters. Information is front-loaded with the core action. Despite length, every sentence serves a necessary function given the lack of schema documentation and annotations. Minor deduction for slight verbosity in the Args section, though justified by the 0% schema coverage.

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?

Comprehensive coverage for a 6-parameter tool with zero annotations and zero schema descriptions. Addresses the tool's role in the ecosystem (workflow integration), output artifacts (.md files and pages.jsonl), and behavioral constraints. Since an output schema exists (per context signals), the brief mention of output files is sufficient.

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

Parameters5/5

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

The schema has 0% description coverage, requiring the description to compensate fully. The Args section provides rich semantic detail for all 6 parameters: examples ('https://docs.example.com/'), value guidance ('Use lower values (10-20) for quick previews'), format implications ('preserves headings, code blocks'), and technology context ('Required for React/Vue/Angular sites').

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 opens with a specific verb and resource ('Crawl a website and save extracted content as clean Markdown or plain text'), clearly distinguishing it from siblings like 'read_page' (single page) or 'extract_data' (data extraction). It further clarifies the scope by mentioning boilerplate stripping and robots.txt respect.

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?

Explicitly states when to use ('when asked to research, read, analyze, or archive a website') and provides a clear workflow sequence ('crawl_site → list_pages or search_pages → read_page'). Critically, it notes the dependency relationship: 'The output_dir from this tool is required by search_pages, read_page, list_pages, and extract_data', which is essential for correct orchestration.

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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