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Glama

Huffines for Comptroller AI Gateway

Get article

get_article
Read-onlyIdempotent

Fetch the full clean text of one article by its slug (the last path segment of an article URL).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesArticle slug, e.g. "my-article-title"

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
dateNo
slugYes
textNo
titleYes
summaryNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds the 'full clean text' detail and the slug derivation, but does not disclose potential errors, availability, or output shape beyond what annotations and output schema already imply.

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?

Single sentence with no filler. The core action, target resource, and key identifier detail are all front-loaded and immediately usable.

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?

This is a simple one-parameter retrieval tool with full annotation coverage and an output schema. The description provides all necessary context for an agent to select and invoke it correctly.

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 schema already documents the slug parameter and gives an example. The description adds extra meaning by defining slug as 'the last path segment of an article URL,' which helps an agent construct the correct value without external knowledge.

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 states a specific verb ('Fetch'), a precise resource ('full clean text of one article'), and the exact identifier ('slug'). It clearly distinguishes this from sibling search/list tools by focusing on a single article retrieval by slug.

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 intended use is implied: call this when you already have an article slug and need the article's text. However, it does not explicitly mention when not to use it or point to alternatives such as search_articles or list_recent_articles.

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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