Explain Choice

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

Annotations already declare readOnlyHint=true and idempotentHint=true, indicating safe, repeatable reads. The description adds behavioral context by naming the specific scoring methods (token matching, fuzzy, etc.), which goes beyond the structured annotations without contradiction.

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 a single, well-structured sentence that conveys the essential purpose and scope without any wasted words. It is front-loaded and efficient.

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 presence of both output schema and annotations, the description effectively covers the tool's core function. It explains what the tool does and the key aspects of its output (scoring breakdown), though it could briefly mention that all parameters are optional.

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 parameter meanings. The tool description adds no new parameter-level detail beyond the schema. Baseline 3 is appropriate as the description does not need to compensate for missing schema info.

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 explains the scoring breakdown for a provider search, detailing specific matching types (token, fuzzy, semantic, metadata). This distinguishes it from sibling tools like opendata_providers_find which likely list results without explanation.

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 implies use after a search to get ranking explanations but does not explicitly state when to use this tool over alternatives, nor does it provide any 'when not to use' guidance. The context is clear but lacks explicit differentiation or prerequisite info.

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