search_vehiclesLook up matching trims in the ScrapAutos curb-weight database for a given year/make/model. Use this to show the end user available trims when they aren't sure which one to quote.
| Name | Required | Description | Default |
|---|---|---|---|
| make | Yes | ||
| year | Yes | ||
| model | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It mentions the 'curb-weight database' but does not explicitly state the tool is read-only or disclose any behavioral traits like rate limits or data freshness.
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 concise sentences with no filler—every word contributes to understanding the tool's purpose and usage.
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 and no description of the return format (e.g., list of trim names/IDs), the description is incomplete for an AI agent to fully understand what it will receive.
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 0%. The description mentions 'given year/make/model' but does not add format specifications, allowed values, or examples, leaving meaning minimally beyond the parameter names.
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 clearly states the tool does a 'look up' of 'matching trims' for a given year/make/model, distinguishing it from sibling tools like get_vehicle_quote which likely provides quotes for a specific trim.
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?
The description explicitly says 'Use this to show the end user available trims when they aren't sure which one to quote,' providing clear context for when to invoke this tool versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool has a clearly distinct purpose: getting a quote, listing rates, searching trims, and submitting a lead. The descriptions clarify boundaries, especially between search_vehicles and get_vehicle_quote.
All tool names follow a consistent verb_noun pattern with snake_case: get_vehicle_quote, list_provincial_rates, search_vehicles, submit_lead. Verbs are descriptive and uniform.
With 4 tools, the set is well-scoped for the domain of scrap vehicle quotes. Each tool covers a necessary step without redundancy or clutter.
The tool set provides a complete workflow: search trims, get a quote, view regional rates, and submit a lead. No obvious gaps exist for the intended purpose.