Explains how each economic figure is calculated: data sources, join keys, scope, year, FX and missing-value defaults, and the parameters that change them. Answer "how did you get that?"
How every number is produced: sources, join key, scope/year/FX/missing-value defaults, and which parameters change them. Use this to answer "how did you get that?".
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full disclosure burden, and it does describe what the response covers (sources, join key, defaults, parameter overrides). It does not mention that it takes no input or that it returns a static documentation payload, but for a no-side-effect provenance tool the disclosure is otherwise adequate.
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?
Two tightly packed sentences with the payload contents front-loaded and the usage trigger appended. Every clause earns its place and nothing is repeated from the schema.
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?
No output schema exists, so the description must convey the return content, and it does so with a specific inventory of topics. It could be slightly clearer that the tool requires no arguments, but an agent has everything needed to call it correctly.
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?
Zero parameters, so the baseline is 4. The description notes that the methodology covers 'which parameters change them', tying the documented defaults back to the parameters of the sibling data tools, which is useful framing even though this tool itself accepts nothing.
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?
The description states exactly what the tool returns — how numbers are produced, including sources, join key, scope/year/FX/missing-value defaults. It implicitly distinguishes itself from the data-retrieval siblings by being the provenance/documentation source, though it never states a verb like 'returns' or names itself as documentation.
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?
It gives a clear use case with a quoted trigger phrase ('how did you get that?'), which tells the agent precisely when to reach for this tool rather than a data sibling. It stops short of when-not guidance or naming the alternative data tools explicitly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.