hm_modelsLists models for a specified brand, returning model slugs and trim types to use in price lookups and car-search queries.
List the models of one brand with their slugs and trims (types).
Use after hm_brands. Model slugs go to hm_prices (market prices, which also lists the trims) and hm_search_cars (cars for sale).
| Name | Required | Description | Default |
|---|---|---|---|
| brand | Yes | Brand slug from hm_brands, e.g. kia, saipa, irankhodro. |
Changes observed during successful MCP inspections.
v0.1.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description contributes beyond them by sketching the payload (slugs plus trims) and by explaining where its output is consumed. It stops short of saying what happens with an unknown brand slug, which is the main remaining behavioral gap.
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 short sentences with no filler; the core operation is front-loaded and the workflow/routing note follows. Every clause earns its place.
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 single-parameter read tool with rich annotations and no output schema, the description covers purpose, ordering, return content and downstream use. Minor gaps: no indication of behavior for an invalid slug and only a brief sketch of the returned structure (whether trims are nested objects).
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% and the schema already spells out the brand slug with examples (kia, saipa, irankhodro). The description only reinforces the cardinality ("one brand") and does not add format or matching semantics beyond the schema. Baseline 3 applies when the schema does the heavy lifting.
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 and resource with scope: "List the models of one brand with their slugs and trims (types)." The one-brand scope plus the mention of slugs and trims distinguishes it clearly from hm_brands (brands) and hm_prices/hm_search_cars (prices, listings).
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?
Explicitly sequences the tool ("Use after hm_brands") and names the two downstream consumers of the output ("Model slugs go to hm_prices ... and hm_search_cars"). This gives the agent both a prerequisite and the follow-on routing decision, not just implied context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.