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

Annotations already declare readOnly/idempotent/non-destructive, and the description stays consistent while adding useful context: what the agent will see back (prices, current real paid availability, input limits, free preview links) and that no purchase or execution happens. It stops short of describing pagination or result-count behavior beyond the limit parameter, so not a full 5.

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?

Four short sentences, front-loaded with the selection condition and the alternative; each sentence carries distinct information. The list of returned data points is dense but relevant rather than padding.

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 only two parameters, no output schema, and full annotation coverage, the description supplies what an agent needs: input model, what data comes back, and a guarantee of no side effects. Only the undocumented 'limit' behavior keeps it short of complete.

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 only 50%: 'query' is documented in the schema, but 'limit' has no description anywhere. The description reinforces the query semantics (capability or product keyword, matching the 'slug or module kind' note) but never explains the result cap, so it does not compensate for the coverage gap.

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 ('find relevant KEVAREMESH-owned APIs and their original contracts') and immediately distinguishes the tool's input model (keyword-driven) from the intent-routing sibling. An agent can identify this tool 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?

It gives an explicit selection condition ('when an AI already knows a capability or product keyword'), names the alternative for the other case ('For a natural-language job choose kevaremesh_route_intent instead'), and adds a scope exclusion ('No purchase or execution occurs here'). Nothing about when to use vs. avoid it is left to inference.

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