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get_event

One AI-news event by slug: full editorial summary plus its outbound coverage list (links to original outlets).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently states what the tool returns ('full editorial summary plus its outbound coverage list'), which is helpful. However, it does not mention failure modes (e.g., what happens if the slug does not exist), authentication requirements, or any side effects. For a read-only lookup, this is acceptable but not comprehensive.

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?

The description is a single, tightly composed sentence that front-loads the primary purpose and the distinguishing output. Every word contributes to the meaning, and there is no filler or repetition. This is exemplary conciseness.

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 simple get-by-slug tool with one parameter and no output schema, the description covers the essential elements: what resource it retrieves, by what identifier, and what it returns. The only missing context is error handling or edge cases, but these are not critical for a straightforward lookup. The description is sufficiently complete for an agent to invoke it correctly.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for parameter documentation. The description only says 'by slug', which clarifies that slug is the identifier but adds no meaning about its format, how to obtain it, or any constraints beyond the schema's maxLength. This is minimal added value over the raw schema.

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-action ('One AI-news event by slug') and specifies the resource ('AI-news event') and the exact output (editorial summary plus outbound coverage list). This distinguishes it from siblings like search_news (search) and related_stories (related content) because it is a direct singular fetch by unique identifier.

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 makes it clear that this tool is for retrieving a single event when you already have a slug, which is a concrete usage context. However, it does not explicitly state when not to use it or mention alternative tools (e.g., use search_news when you need to find events by query). The absence of explicit exclusions is a minor gap, but the implied condition ('by slug') is sufficient for basic 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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