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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds valuable behavioral context: it returns an array of {period, value} observations, describes period date formats (YYYY, YYYY-QN, YYYY-MM), states no API key is required, and mentions the CC-BY 4.0 license. This goes beyond the annotations and helps the agent understand response shape and constraints.

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 four sentences, front-loading the core purpose and output format, then giving examples and an optional parameter. No redundant fluff, though the list of agencies could be seen as slightly verbose. It is structured well: purpose → return type → period formats → examples → optional parameter → data coverage/licensing.

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 that an output schema exists and annotations cover safety, the description is complete for a read-only data-fetch tool. It states what is returned, period formats, an optional limiting parameter, examples of valid codes, and the open-data licensing. No critical missing context for an agent to invoke it 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%, so the schema already documents all parameters with examples and cross-references. The description adds a brief explanation of last_n_periods ('limit output to the most recent N observations') and provides example codes in context, but the schema descriptions hold the same information. Baseline 3 is appropriate because the description supplements but does not add significant new meaning.

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 uses the specific verb 'Fetch' and clearly identifies the resource: 'full time-series history for a specific series from DBnomics.' It provides concrete examples with provider/dataset/series codes)Skip the description? Already did. It distinguishes from sibling tools that browse providers/datasets/series by focusing on a single series's data.

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 clearly implies the use case: call this when you have a specific series and need its full observation history. It mentions the optional last_n_periods parameter to limit output, which guides usage. However, it does not explicitly exclude alternatives or mention when not to use other dbnomics tools, though the context is clear enough.

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