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JavaScript
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denverpost_sections

List the 56 Denver Post editorial sections and 19 topic archive slugs accepted by the headlines endpoint, with names and URLs, to build valid queries.

Instructions

Get Denver Post section and topic inventory. Lists the Denver Post slugs that the headlines endpoint accepts: 56 editorial sections and 19 topic archives, checked on 2026-09-30. Examples are colorado, denver-broncos, economy and hiking. Each entry has a slug, name and url. Branded content and cartoons are left out.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.9

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well: it discloses read-only inventory semantics, the freshness date ('checked on 2026-09-30'), the entry fields, and the exclusion of branded content and cartoons. It does not mention auth or rate limits, but for a static lookup list that is a minor gap.

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?

Four tight sentences, front-loaded with purpose, then coverage counts, examples, return fields, and exclusions. Every sentence adds information, though the example slugs and date could be trimmed without much loss.

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?

No output schema exists, so the description compensates by describing the returned entry shape ('slug', 'name', 'url'), the scope (56 sections, 19 topic archives), and what is omitted. Nothing an agent needs to call and interpret this tool is missing.

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

Parameters4/5

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

The tool takes zero parameters, so the baseline is 4; there is no parameter surface for the description to explain and none is needed.

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?

States a specific verb ('Get') and resource ('section and topic inventory') and immediately clarifies that it enumerates the slugs the headlines endpoint accepts. An agent can distinguish this discovery tool from the actual headlines retrieval without opening either schema.

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 phrase 'slugs that the headlines endpoint accepts' makes the use case clear: fetch valid section/topic identifiers before querying headlines. It stops short of naming the sibling (denverpost_headlines) or stating the when-not, so it is strong context rather than explicit 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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