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lyrenth

Lyrenth

Official

Read URL

read_url
Read-onlyIdempotent

Retrieve and convert any public web page into a clean Markdown AIDocument containing title, description, and structure, stripping navigation and boilerplate.

Instructions

Read any public web page as a clean AIDocument: Markdown plus title, description, and structure, with navigation and boilerplate stripped. Prefer this over a raw HTTP fetch whenever you need the content of a web page; it returns far cleaner, lower-token text. Powered by Lyrenth.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesAbsolute http(s) URL of the page to read.
freshNoForce a fresh fetch instead of the cached version. Slower; default false.
max_tokensNoCap the returned content to roughly this many tokens, trimmed at a clean paragraph or sentence boundary. Use it when you have a tight context budget.
Install Server

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already establish the tool as read-only, idempotent, and non-destructive. The description adds valuable behavioral context: it strips navigation and boilerplate, returns lower-token text, and produces a structured AIDocument rather than raw HTML. It does not contradict the annotations, though it omits details about error behavior, redirects, or non-HTML content.

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?

The description is only two sentences and front-loads the purpose and output format before giving usage guidance. The phrase 'Powered by Lyrenth' adds little operational value, but the overall text remains concise and easy to parse.

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?

For a read-only tool with rich annotations and fully documented parameters, the description gives sufficient context to select and invoke it correctly: it explains what content is read, what output form is returned, and when to prefer it. It lacks explicit edge-case behavior and does not route to the sibling 'read_urls', but these are minor given the schema and annotations.

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%, with all three parameters (url, fresh, max_tokens) already documented in the input schema. The tool description adds no extra parameter semantics beyond what the schema provides, so the baseline of 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 opens with a specific verb and resource: 'Read any public web page as a clean AIDocument,' and details the output form (Markdown plus title, description, structure, stripped boilerplate). It clearly defines what the tool does, though it does not explicitly contrast itself with the sibling 'read_urls', leaving some differentiation to the tool name and plural form.

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 explicitly says to 'Prefer this over a raw HTTP fetch whenever you need the content of a web page,' giving a clear when-to-use signal and naming an alternative. It does not state when not to use it or when to choose the sibling 'read_urls', so exclusions and sibling routing are incomplete.

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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