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

Annotations already declare readOnly/idempotent/non-destructive, so 'Read-only' is redundant. The description earns credit for going beyond them: it discloses data provenance (commissioned vs PlasticList-derived) and imposes a reporting duty ('report which'), plus the sample-vs-unit caveat. It stops short of describing result/pagination shape.

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?

Front-loaded purpose followed by tightly packed caveats; nearly every clause adds decision-relevant information. Minor waste in restating 'Read-only' which annotations already assert.

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 10-parameter search with no output schema, the description covers scope, provenance, and analytical limitations well. It could say more about what a result row contains and how cursor pagination sequences, which is the remaining gap.

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 90%, so the schema already documents all 10 parameters including the analyte/detected interaction and cursor semantics. The description adds no parameter-level syntax or format detail beyond what the schema provides; baseline 3 applies.

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?

States a specific verb+resource ('Search ... published product-test records') and immediately scopes the corpus (commissioned vs PlasticList-derived). An agent can distinguish it from the singular get_result sibling without opening either schema.

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?

Gives an explicit usage trigger ('Use this before answering whether a product, brand, or category has been tested'), a scope exclusion for microplastics, and points to list_analytes as the source of analyte values. Both when-to-use and when-not-to-use are covered.

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