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Highland Intel APIs

Web page to Markdown

page-markdown
Read-only

Fetches a public page and returns clean, LLM-ready Markdown of the main content, with title, word and link counts. No third-party scraper. Returns { url, title, words, links, truncated, markdown } Price: 3 credits (1 credit = 1 CAD cent) per successful call; input that does not match the schema is rejected before billing.

Input Schema

NameRequiredDescriptionDefault
urlYesPublic http(s) URL to fetch. Private and internal hosts are refused.
max_charsNoMarkdown kept, default 20,000.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered; the description goes further by disclosing the exact return shape, the pricing/credit model, that billing only applies to successful calls, and that schema-invalid input is rejected pre-billing. That is real operational context an agent cannot get from structured fields, though error behavior and JS-heavy page handling remain unstated.

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?

Front-loaded with the purpose before the mechanics, and the pricing caveat is short and useful. There is minor redundancy — "with title, word and link counts" is restated in the field list — but nothing is padded.

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

Completeness4/5

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

With no output schema, the description correctly compensates by enumerating the return object, including the `truncated` flag that signals max_chars clipping. Coverage of pricing, host restrictions, and output shape makes it callable without guessing; only failure modes and truncation semantics beyond the field name are absent.

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 coverage is 100% — both `url` (public http(s), private hosts refused) and `max_chars` (default 20,000, cap 50,000) are already documented in the schema. The description adds no parameter-level detail 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.

Purpose4/5

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

The description uses a specific verb and resource ("Fetches a public page and returns clean, LLM-ready Markdown of the main content") and names the return fields, so the job is unambiguous. It stops short of explicitly naming a sibling such as web-scrape or web-extract, so an agent must infer the boundary itself.

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

Usage Guidelines2/5

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

The only scoping signal is implicit — the page must be public, since "Private and internal hosts are refused" (in the schema). There is no statement of when to choose this over web-contents, web-extract, web-scrape, or enrich-url, all of which fetch or transform web pages, and no guidance on when it is inappropriate.

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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