Product reviews

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

Annotations already declare readOnly/idempotent/non-destructive, so safety is covered; the description adds genuinely useful behavior: results are sorted newest first and include the store's replies plus a star breakdown. It does not cover pagination or result-size behavior, keeping it just short of fully transparent.

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 compact paragraphs with the resource and ordering constraint front-loaded. The trailing sentence on aggregate-field semantics is slightly output-schema territory given an output schema exists, but it earns its place by disambiguating count vs. the filter.

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 read-only, well-annotated tool with full schema coverage and an output schema, the description supplies everything an agent needs: the resource, sort order, what is included, and the intended use case. No material gap remains.

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%, so the baseline is 3, but the final sentence adds meaning the schema does not: average and star_counts span ALL reviews while count reflects only those matching `stars`. That resolves a real ambiguity in how the aggregate fields relate to the `stars` filter.

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 names a specific verb and resource ('Read customer reviews of a product') and scopes it precisely with ordering (1-5 stars, newest first) and included data (store replies, star breakdown). An agent can distinguish this from mk_product, mk_specs, or mk_blog_comments without opening any 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?

'Use as a quality check before recommending a product' gives a clear when-to-use scenario, which is more than most read tools provide. It stops short of naming when not to use it or pointing to sibling tools for related data (e.g., mk_product for the product itself).

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