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Blackwood State

Web page to Markdown

web-markdown_v1
Read-onlyIdempotent

Returns JSON with the clean Markdown of a public web page plus its title, description, language, canonical URL and links. Use when you need to scrape a web page, extract content from a url or read an article as markdown for an LLM. Do not use when the page needs JavaScript to render, sits behind a login or paywall, or is not HTML (use a PDF reader for PDFs). Price: 0.01 USDC per call. Typical response time: 2500 ms (p95).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic http(s) URL of the web page to read
maxCharsNoMaximum length of the returned markdown (500-100000 characters, 50000 when omitted)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/openWorld semantics, so the safety profile is covered; the description goes further by disclosing cost (0.01 USDC per call), p95 latency (2500 ms), and the concrete failure modes (no JS rendering, no paywall/auth, HTML only). That is behavioral context an agent cannot get from the structured fields.

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?

It is compact and dense: return shape, usage, exclusions, price, and latency each occupy their own sentence with no filler. Minor redundancy in the triple synonym 'scrape a web page, extract content from a url or read an article', and the leading sentence describes returns before the action, costing it the top score.

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?

With an output schema present and annotations covering safety, the description needs only routing, cost, and latency to be complete for a two-parameter read tool — and it supplies all three plus the limitations. An agent has everything needed to decide whether to call it and what to expect.

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

Parameters3/5

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

Schema description coverage is 100% for both parameters, so the schema already documents the URL format and the maxChars range/default. The description adds no parameter-level meaning beyond what the schema provides, so the baseline 3 applies.

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 gives a specific verb+resource (fetch a public web page and return clean Markdown) and enumerates the payload (title, description, language, canonical URL, links). It also draws a clear boundary against the nearest sibling by name of function ('use a PDF reader for PDFs'), so an agent can distinguish it from pdf-text_v1 without opening the schema.

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?

It states explicit use cases ('scrape a web page, extract content from a url or read an article as markdown for an LLM') and explicit exclusions (JavaScript-rendered pages, login/paywall, non-HTML content) with a routing hint to the PDF alternative. Both the when and the when-not are spelled out rather than implied.

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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