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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. The description adds a valuable behavioral detail: 'The most recent observation in the returned array is the current value,' which clarifies output ordering and how to extract the latest data point. No contradictions with 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?

The description is well-structured and front-loaded, with a clear first sentence followed by a bulleted list of five specific, actionable examples. The final note about the most recent observation is a critical piece of usage information. No fluff or redundant content; every line earns its place.

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?

Given the tool's moderate complexity, rich annotations, complete parameter schema, and presence of an output schema, the description covers the core purpose, provides common use cases, and clarifies output interpretation. It could be slightly more explicit about how it relates to sibling tools, but overall it is sufficiently complete for an agent to use 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% with both parameters fully described, including enums and guidance like 'Use 30 for current/recent values.' The description's examples reinforce common series_id/day combinations but do not add substantial semantics beyond what the schema already provides, so a baseline score of 3 is appropriate.

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 clearly states the tool returns recent observations for any supported FRED data series, listing a wide range of economic indicators. This distinguishes it from sibling tools like get_current_value or get_value_by_date that focus on single values or specific dates, though it does not explicitly name these alternatives.

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 description provides clear context for when to use the tool ('Use this to get current and historical values') and includes five concrete common use cases with exact series_id and days parameters. It does not explicitly mention when not to use it or name alternative tools, but the examples give strong practical guidance.

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