get_series

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

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true. The description adds behavioral detail about the returned fields but doesn't contradict annotations. Without annotations, this would score higher, but annotations reduce the burden.

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 a single sentence with no wasted words. It front-loads the action ('Fetch metadata') and specifies the key parameter and example outputs. Perfectly concise.

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 single parameter, rich annotations, and no output schema, the description is largely complete. It could optionally mention that the result is a JSON object, but this is implicitly understood from the purpose. No major gaps.

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?

There is one parameter (series_id) with 100% schema coverage. The description adds value by providing examples (GNPCA, UNRATE) and explaining it's the FRED series id. This is helpful 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 clearly states it fetches metadata for a FRED series by id, listing specific fields (title, frequency, seasonal adjustment, units, observation date range, popularity). This distinguishes it from siblings like get_observations (data) or search_series (search).

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 implies usage for fetching metadata when you have a specific series id. It doesn't explicitly state when not to use or name alternatives, but the context from sibling tools clarifies its role. Some guidance on when to prefer search_series would improve it.

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