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latimes_article

Retrieve Los Angeles Times article metadata and body paragraphs from a canonical article URL using NewsArticle structured data.

Instructions

Get Los Angeles Times article content. Returns a Los Angeles Times article's public metadata and body paragraphs from a canonical article URL, read from the page's NewsArticle structured data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesCanonical Los Angeles Times article URL

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.5

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden and largely meets it: it explicitly says the operation reads public metadata and body paragraphs from NewsArticle structured data, establishing a read-only, public-access profile. It does not mention failure modes, paywalls, or formatting, but for a simple public fetch tool the disclosed behavior is sufficiently transparent.

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?

Two well-formed sentences with no filler. The core action and return type are front-loaded, and the source detail is placed second where it adds value without bloating the description.

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 one-parameter read tool with no annotations, the description is nearly complete: it identifies the input, the source of data, and the returned content. It lacks exact field-level output details since there is no output schema, but that is a minor gap for an article-fetching tool of this simplicity.

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%: the single url parameter is already fully described as 'Canonical Los Angeles Times article URL.' The description's mention of 'canonical article URL' only reinforces the schema without adding new semantic detail, so the baseline of 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 names a specific verb and resource: 'Get Los Angeles Times article content.' It goes beyond a tautology by specifying the return payload (public metadata and body paragraphs) and the input source (canonical URL), which clearly distinguishes it from sibling tools like latimes_author, latimes_headlines, and latimes_sections.

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 description gives no explicit guidance about when to choose this tool over siblings or alternatives. It implies the tool is for fetching a known article by URL, but it never states exclusions or points to latimes_author/headlines/sections for other intents. An agent must infer when this is the right article-content tool.

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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