bls_search_series

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds context that the tool returns curated 'popular' IDs, implying a limited set rather than exhaustive coverage. This helps the agent understand the tool's scope. There's no contradiction with annotations, and the added value is meaningful but not extensive.

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 efficient: two sentences and a topic list. The purpose is front-loaded, the rationale is brief, and the topic enumeration is necessary for parameter completeness. There is no waste or verbosity, making it easy to parse quickly.

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?

For a simple lookup tool with 2 parameters (one optional) and no output schema, the description is nearly complete. It clearly states it returns series IDs, and the topic list covers all valid values. The only missing piece is an explicit connection to follow-up tools like bls_series_data, but that is inferable. Overall, an agent can correctly invoke this tool with the information provided.

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 both parameters (topic and state) are already documented with clear descriptions. The tool description repeats the topic list and mentions state-level data, but adds no new meaning beyond the schema. With high coverage, the baseline of 3 is appropriate; the description doesn't compensate for anything missing.

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 verb ('Look up'), the resource ('popular BLS series IDs'), and the scope ('by topic'). It distinguishes itself from sibling tools like bls_series_data (which fetches data for a given ID) and bls_employment_by_industry (which provides breakdowns) by focusing on curated ID lookup. The purpose is immediately understandable and specific.

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 explains why this tool exists ('BLS doesn't have a search API, so this provides curated series IDs') and lists valid topics. It implicitly guides the agent to use this tool to obtain series IDs before fetching data, but it does not explicitly exclude alternatives or state when not to use it. The context is clear enough, but exclusions are left to inference.

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