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ptrken01

searxng-mcp-scraper

by ptrken01

scrape_blog

Discover all posts on a blog and write them into one aggregated Markdown file. Uses RSS/Atom feeds or HTML crawling to find post URLs, then fetches and cleans each article's text.

Instructions

Discover every post on a blog and write a single aggregated Markdown file.

Tries the blog's RSS/Atom feed first (common paths like /rss.xml,
/feed, /atom.xml). If no feed responds, crawls the HTML index
(up to blog_scrape_discovery_pages pages). Each discovered post
URL is fetched in parallel and its cleaned main text is appended
to one Markdown file at:

  {blog_scrape_output_dir}/<safe-host>_<safe-path>_<unix-ts>.md

The file starts with YAML front matter (blog URL, post count,
byte total, duration) followed by one H3 section per post with
its title, original URL, published date (if known from the feed),
content-type, byte count, and the cleaned text. Failures are
noted in-band as `- Fetch error: <code>` bullets, not by aborting
the whole run.

Args:
    blog_url: Root URL of the blog (e.g. "https://blog.example.com/").

Returns:
    Small summary dict — never the file contents:
      {blog_url, output_path, post_count, post_count_ok, byte_count,
       duration_s, discovery}
    On failure: {blog_url, error: <stable_code>, message}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ctxNo
blog_urlYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations, the description fully carries the behavioral burden. It discloses the two-phase discovery strategy, parallel fetching, output file location and naming, YAML front matter contents, in-band error handling ('- Fetch error: <code> bullets, not by aborting'), and that the return value is a summary dict, never the file contents. This is exemplary transparency.

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

Conciseness5/5

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

The description is long but every sentence earns its place, covering purpose, algorithm, output format, error handling, arguments, and return value. It is front-loaded with the core purpose and uses structured headings (Args, Returns) for scannability.

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?

For a tool with two parameters, no annotations, and an output schema, this description is remarkably complete: it explains discovery limits, output path, file structure, in-band error behavior, and the exact return dict on both success and failure. It leaves no critical operational gap.

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 description coverage is 0%, so the description must compensate. It explains the only meaningful parameter, blog_url, with type, purpose, and an example. The ctx parameter is auto-injected and left unexplained, but this is acceptable; the description adds substantial meaning beyond the sparse schema.

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+resource+action: 'Discover every post on a blog and write a single aggregated Markdown file.' It clearly distinguishes this from sibling tools like fetch (single-page fetch) and search (web search) by emphasizing blog-wide discovery and file output.

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

Usage Guidelines4/5

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

The description implies the use case: use this when you want all posts from a blog aggregated into one Markdown file. It details the strategy (RSS/Atom first, then HTML crawl) but does not explicitly state when to prefer this over alternatives or when not to use it, so it falls just short of a 5.

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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