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

The annotation set the read-only and non-destructive base, and the description adds real behavioral depth: data sources, number of FRED series, bucket organization, what the output contains, and update cadence. Nothing in the description contradicts the annotations.

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?

Three dense but focused sentences carry the whole picture: what the tool is, what data it includes, and how current the data is. There is no padding or repetition of schema content.

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 tool with one documented optional parameter, one read-only annotation, and no output schema, the description provides enough context for an agent to understand the output shape selection and freshness expectations. The missing pieces are minor and are already covered by the schema.

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 schema already explains the single optional parameter and its allowed values. The description reinforces the conceptual meaning by naming the two monitors being configured, but it does not add fully novel parameter detail beyond that baseline.

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 is specific about what the tool brings back and which data it combines: Structural Inflation and Growth & Recession monitors with scores, regimes, direction, recession risk, and z-scores. This clearly separates it from similar-sounding offerings like get_factor_regime.

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?

The intended use is strongly implied: this is the tool for the Closelook macro inflation and growth regime reads. However, it does not explicitly state when not to use it or point to sibling alternatives, so the agent must infer the routing from context.

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