Skip to main content
Glama

DataClue — AI training data

Get pricing and terms

get_pricing_and_terms
Read-only

DataClue's list prices, what is included, quote paths (free samples, paid pilot, volume quote, custom collection), licensing, payment and consent terms.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, so the safety profile needs no restating. The description still adds value by scoping the exact content covered, though it says nothing about freshness, sourcing, or rate limits.

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?

A single dense sentence with no filler, and the core content (prices) is front-loaded. It reads as a noun list rather than a verb-led statement of purpose, which slightly weakens the structure.

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?

With no output schema, the description carries the burden of describing return content, and its enumeration of price, inclusions, quote paths, licensing and payment terms does that well. Missing only framing details like return format or how current the data is.

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?

Zero parameters, so per the baseline this scores 4. There is nothing parameter-related for the description to compensate for.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the resource precisely (list prices, inclusions, quote paths, licensing, payment and consent terms) so an agent knows exactly what content it returns. It doesn't explicitly contrast itself with siblings like request_quote, so the distinction is inferable rather than stated.

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?

Listing 'quote paths (free samples, paid pilot, volume quote, custom collection)' implies this is the informational lookup that precedes the action tool request_quote, but no explicit when-to-use or when-not-to-use guidance is given. The agent must infer that request_quote is the sibling to call for the actual quote.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources