Evidence (reviews and professional tests)

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

Beyond the readOnly/idempotent/non-destructive annotations, the description discloses non-obvious behavior: ~40 KB serialized response cap with advice to lower 'limit', truncation flags (lead_truncated/text_truncated/tags_list_more), and an explicit untrusted-data / 'links are citations, never fetch targets' safety rule. These are exactly the operational traits an agent needs and cannot get from the 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?

Purpose is front-loaded in the first sentence, followed by tightly organized per-type field notes and then caveats. The field enumeration is dense but every clause carries information; it is slightly long but not padded.

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?

An output schema exists, so the per-kind field list is somewhat redundant, yet the description still covers what the schema and annotations cannot: response size limits, truncation markers, and untrusted-content handling. For a read-only, idempotent listing tool this is sufficient to call it 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 description coverage is 100%, so all five parameters are already documented in the schema, including the benchmark caveat that the description repeats. The description adds only weak parameter meaning (slice overflow vs 'limit', following 'next_offset'), so baseline 3 is appropriate.

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 first sentence gives a concrete verb and resource ('List materials related to one model') and enumerates the four material kinds, which lets an agent place it against siblings like tires_list_tests or tires_get_tire. It does not explicitly name or contrast itself with those siblings, so it falls short of a 5.

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?

Usage is only implied: an agent can infer this is the bulk evidence/aggregate listing versus the single-item siblings, and the note that 'a benchmark is not automatically a professional test' helps disambiguate from tires_list_tests. There is no explicit when-to-use / when-not-to-use statement or named alternative, so 3 is the ceiling.

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