bls_series_data

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

The annotation readOnlyHint: true already covers the read-only nature. The description adds useful behavioral context by noting the frequency (monthly/quarterly/annual) and scope of data (employment, wages, prices). It does not contradict annotations and provides enough additional insight beyond the structured data.

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 well-structured and front-loaded with the core purpose. It includes a concise lead sentence, a bulleted list of popular series IDs with explanations, and a clear prefix legend. No unnecessary repetition; every element adds value.

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 tool's complexity (many possible series IDs) and the absence of an output schema, the description provides substantial context through examples and prefixes. It could mention the response format, but the description is otherwise complete enough for an agent to select and invoke the tool 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 descriptions cover all parameters (100%), serving as a solid baseline. The description goes further by listing popular series IDs and explaining prefix meanings (CES, LNS, CU, etc.), which significantly aids in correctly constructing the series_ids parameter and understanding the start_year/end_year context.

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's function: "Fetch time series data from the Bureau of Labor Statistics." It specifies the resource (BLS) and the action (fetch), and provides concrete examples of series IDs and data types (employment, wages, prices), which distinguishes it from other BLS-related tools like bls_search_series or bls_employment_by_industry.

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 does not explicitly state when to use this tool versus alternatives. It implies usage by providing popular series IDs and prefixes, but gives no exclusions or references to sibling tools (e.g., 'use bls_search_series to find IDs'). This is adequate but lacks comparative guidance.

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