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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so the safe/idempotent profile is covered. The description adds only that results are 'verified' and come from compatibility data; it says nothing about permissions, rate limits, or result ordering, which the annotations do not cover.

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 sentences, the resource and data scope front-loaded, and the usage cue placed last. Nothing is redundant or 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?

With no output schema, the description still should suffice: the schema documents all inputs and annotations carry the safety profile. Only minor gaps remain, such as how results are ordered or whether the model parameter must match exactly versus fuzzily.

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 (brand, limit, model, query, agent_id) are already documented with examples and constraints. The description adds no syntax, matching behavior, or format detail beyond the schema, so 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 (find) and resource (verified spare parts) scoped to a heat-pump model and named data source ('Energirör's compatibility data'). It is clear what the tool returns, though it never contrasts itself with the close sibling search_spare_parts, so sibling differentiation is left to inference.

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 condition: 'Use this before recommending a part for a named model.' That is a clear when-to-use cue, but there is no when-not-to-use and no named alternative (e.g. search_spare_parts for free-text lookup), so the routing guidance is incomplete.

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