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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context by specifying the return contents (both observations, dollar change, percent change, series definitions, release provenance, source hashes) and clarifying that this is descriptive historical arithmetic.

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?

The description is front-loaded with the core calculation, then return details, then concrete examples. Every sentence earns its place by either clarifying scope, output, or intended use.

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?

With no output schema, the description usefully summarizes return values. The input schema fully documents parameters, and annotations cover safety and idempotency, so the definition is complete enough for an agent to select and invoke the tool 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?

Schema description coverage is 100%, so the schema already documents parameter formats such as 'Exact curated slug or official Z.1 series ID' and 'YYYY:Qn'. The description adds the conceptual constraint of 'one curated Federal Reserve Z.1 aggregate between two exact hosted quarters,' but does not add syntax or format details beyond the schema.

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 a specific verb and resource: 'Calculate the absolute and percentage change in one curated Federal Reserve Z.1 aggregate between two exact hosted quarters.' This clearly distinguishes it from sibling tools like fed_z1_series and fed_z1_snapshot, which retrieve or snapshot a series rather than compute a change between two periods.

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 explicit use cases ('how much did household net worth change...', 'growth in mortgage debt since 2020') and an exclusion ('This is descriptive historical arithmetic, not a forecast or recommendation'). It does not, however, name alternative tools for related tasks such as retrieving raw observations via fed_z1_series.

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