Get FRED series observations

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

Annotations already declare readOnlyHint=true, so the read-only safety profile is known. The description adds useful behavioral context about optional transformations and filters, along with an example call. However, it does not disclose default limits, pagination behavior, or error conditions. It neither contradicts nor deeply extends the annotation.

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?

Two sentences are used effectively: the first states the core action and capabilities, and the second provides a concrete example. The description is front-loaded with the main purpose and avoids any filler or repetition.

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?

While the output schema exists (so return values are covered), the description leaves many advanced parameters unexplained, such as realtime_start/end, vintage_dates, output_type, and aggregation_method. The basic use case is well covered, but the full parameter landscape is not addressed. This is adequate but not complete.

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 0%, and the description only vaguely references 'unit transforms, frequency aggregation, and date filters' without naming most parameters. The example shows series_id and observation_start but ignores 11 other parameters (e.g., units enum, aggregation_method, vintage_dates). This provides only a high-level grouping, insufficient for a 13-parameter tool.

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 gets observations (data values) for a FRED series, using the specific verb 'Get' and resource 'observations for a FRED series.' It also lists key capabilities (unit transforms, frequency aggregation, date filters) that distinguish it from sibling tools like get_series (metadata) 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 when to use the tool (when you need data values for a series) but does not explicitly define when not to use it or mention alternatives. For example, it doesn't say 'use get_series for metadata instead.' The context is clear but lacks exclusions or alternative references.

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