Free, unauthenticated dataset catalog.
Describes every table this service sells, its fields, current pricing, and freshness. Read this before paying for anything.
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "get_catalog"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description still adds genuinely new behavioral context: the call is free and requires no authentication, which is exactly the information an agent needs before spending money on paid calls.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four short lines, front-loaded with the core identity (free catalog) and ending with the actionable instruction. No filler, no repetition of the tool name or annotations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only introspection tool with rich annotations, the description covers what the response contains (tables, fields, pricing, freshness) and why to call it. It doesn't describe response shape or state the catalog's scope/size, but nothing essential to correct invocation is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. The description correctly implies a single unfiltered response rather than suggesting any hidden selectors.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific resource (a dataset catalog) and exactly what it enumerates: every table sold, its fields, pricing, and freshness. That makes it clearly the metadata/introspection tool rather than a data-fetch tool, distinguishable in practice from the sibling lookup/screen/check tools, though no sibling is named explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
"Read this before paying for anything" gives a concrete when-to-use trigger tied to cost. It does not spell out when not to use it (e.g., when you already know the table) or name alternatives, so it stops short of full routing guidance.
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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