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fetch_readable

Extract the main article content from any URL by removing navigation, ads, and sidebars. Falls back to the full page when the article is too short, and supports persistent tabs for session continuity.

Instructions

Load a URL and extract the main article content (removes navigation, ads, sidebars). Falls back to full page content if extraction yields too little text. Supports persistent sessions via tab_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoThe URL to load (optional if tab_id is provided)
tab_idNoReuse a persistent tab (from open_tab) instead of opening a new one
timeoutNoTimeout in ms (default: 30000)
wait_forNoCSS selector to wait for before extraction
max_lengthNoMax content length in characters (default: 30000)
fallback_to_fullNoFall back to full page content if Readability extraction is too short (default: true)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral disclosure burden and does a solid job: it reveals that navigation/ads/sidebars are removed, that it falls back to full page content when extraction is too short, and that persistent sessions are supported. It omits details like output format or side effects, but the key behavioral traits are disclosed.

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?

Three concise sentences, each earning its place. The core behavior is front-loaded, fallback behavior follows, and the persistent-session capability is stated without fluff.

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

Completeness3/5

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

The description covers the core extraction behavior and fallback, but it does not explain the return format despite there being no output schema, nor does it offer guidance on choosing among related sibling tools. It is adequate for basic invocation but leaves notable gaps around output expectations and alternative tool selection.

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%, so the baseline is 3. The description adds only a light conceptual layer about persistent sessions via tab_id, but most parameter meaning is already fully documented in the schema. No compensation needed or provided.

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 clearly states a specific verb and resource: 'Load a URL and extract the main article content.' It also differentiates itself from siblings like fetch_page by emphasizing readability extraction that removes navigation, ads, and sidebars, with a fallback behavior.

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

Usage Guidelines3/5

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

The description implies when to use the tool—when main article content is needed—but never explicitly contrasts it with alternatives like fetch_page or fetch_structured_data. Mentioning persistent sessions via tab_id gives some contextual guidance, but no when-not-to-use or explicit alternative routing.

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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