Search car variants with specs

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

Annotations already cover readOnly, idempotent, openWorld, and non-destructive, so the safety profile is settled. The description adds real behavioral detail beyond that: results are flagged `variant: true` only when specs exist, and brand/model matches are group nodes rather than variants — a non-obvious result-shape rule. It stops short of describing the full result shape or max-result behavior, keeping it below a 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?

Three sentences, front-loaded with purpose and the downstream slug contract, then usage ordering, then the result-flag caveat. No filler, and the most decision-relevant information (use first, returns slug) comes first.

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 carries the return-value burden and does explain the key output (slug) and the `variant: true` marker. It does not describe the remaining fields of a match (name, brand/model grouping labels) or default limit behavior, leaving a small gap for a search tool whose output drives chained calls.

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 both `query` (with Persian/English examples) and `limit` (1-30) are already documented. The description adds no format, syntax, or matching-behavior guidance for the query beyond what the schema states, so the 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?

"Find car variants in Karnameh's specs catalog and return the `slug` that kn_specs and kn_compare_specs take" gives a specific verb, resource, and output, and explicitly positions itself upstream of two named siblings. An agent can tell exactly what this tool produces and what consumes it.

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 first when you want the technical specs, expert review summary or a comparison" states the triggering conditions and implicitly routes to kn_specs / kn_compare_specs as the follow-on calls. The closing sentence adds an explicit recovery rule: if a match is only a brand/model group, refine the query with more words.

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