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

Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses meaningful behavior: it returns pre-computed aggregates, editorial prose when available, canonical citations, and deliberately omits raw historical series. It also provides an alternative source for the missing data, which is valuable transparency.

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 efficiently structured: a front-loaded sentence states the tool's purpose and return contents, followed by a crucial exclusion/alternative and concrete slug examples. Every sentence adds value, and there is no redundant or filler language.

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?

With no output schema, the description carries the burden of explaining return values, and it does so thoroughly by listing fields (latest value, unit, frequency, direction, aggregates, prose, citations). It also addresses the main limitation (raw series not included) and offers an alternative source, making the tool fully contextualized for an agent.

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 has 100% coverage for the only parameter (slug), including format, examples, and a pointer to search_indicators. The description reinforces the slug examples but does not add new parameter semantics beyond what the schema provides, so the 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 opens with a specific verb ('Fetch') and a clearly bounded resource ('compact snapshot of an American Default economic indicator by slug'). It enumerates distinct return contents and explicitly contrasts with the raw historical series API, distinguishing itself from alternatives like get_indicator_v2.

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 clear when-to-use guidance by stating that this tool returns a compact snapshot and that the raw historical series is not included, directing the reader to a direct API URL for full data. It also references search_indicators for slug discovery in the schema description. However, it does not explicitly contrast with sibling get_indicator_v2.

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