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

With no annotations, the description must fully disclose behavior. It only says 'series observations' without mentioning any constraints like date range handling, pagination, error responses, or what the output looks like. This is insufficient for an agent to predict tool behavior.

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 examples, making it very concise and front-loaded. Every word serves a purpose, though it could be slightly more structured with a clearer separation between purpose and examples.

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?

Despite low parameter count and no output schema, the description lacks essential context: it does not explain the output format (e.g., time series data), how date_from/date_to control the range, or any limitations. This makes it incomplete for effective tool use.

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 coverage is low (33%), but the description adds value by giving examples for series_id, which is the main parameter. However, date_to has no description in schema or description, and date_from's schema description is minimal. The examples partially compensate but not fully.

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 retrieves 'St Louis Fed (FRED) series observations' and provides concrete series ID examples (CPIAUCSL, UNRATE, DGS10, FEDFUNDS). This distinguishes it from sibling tools like fred_search_series (search) and World Bank tools.

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 gives examples of when you would use this tool (when you have a series ID like 'CPIAUCSL') but does not explicitly state when to avoid it or when to use alternatives like fred_search_series. Usage context is implied rather than explicit.

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