cms_search

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds value by disclosing what the response contains (IDs, titles, descriptions) and by directing the return value to cms_query. No contradiction with annotations.

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 short sentences carry the full message: what the tool searches, what it returns, and what to do next. There is no filler, and the most important information is front-loaded.

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 tool with one well-documented parameter, safety-bearing annotations, and no output schema, the description is sufficient. It explains the return contents and provides the next step, so an agent can invoke it correctly without missing context.

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 coverage is 100% and the keyword parameter already includes helpful examples. The description adds only 'by keyword,' which repeats the schema rather than deepening the meaning. This meets the baseline for high schema coverage.

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 states a specific action ('Search'), a clear resource ('CMS provider data datasets'), and the exact output shape ('dataset IDs, titles, and descriptions'). It also names the downstream counterpart (cms_query), distinguishing this metadata-discovery tool from the data-fetching sibling.

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 context: it is used to find datasets by keyword, then the returned ID feeds into cms_query. It doesn't mention exclusions like cms_hospitals or cms_nursing_homes, but the workflow guidance is strong enough that an agent knows when this tool is the right step.

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