decode_vinDecode a 17-character Vehicle Identification Number (VIN) into year, make, model, trim, body style, and manufacturer. Use before estimate_vehicle_value to get exact vehicle details.
| Name | Required | Description | Default |
|---|---|---|---|
| vin | Yes | 17-character VIN (letters I, O, Q are not used) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful context about the decoded fields but does not disclose edge-case behavior such as how invalid VINs are handled or whether partial matches are returned.
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 with no filler. The core function is stated first, followed by a useful usage pointer. Every word 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-only decoding tool, the description covers what the tool does, what it returns, and how it fits into the larger workflow with estimate_vehicle_value. No critical information an agent needs before calling it is missing.
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%, including a pattern and length constraints for the vin parameter. The description restates '17-character' but does not need to add much more because the schema already defines the parameter clearly.
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 states a specific verb ('Decode'), a specific resource (17-character VIN), and the exact outputs (year, make, model, trim, body style, manufacturer). It also distinguishes itself from estimate_vehicle_value by identifying itself as the prerequisite step.
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 tells the agent to use this tool before estimate_vehicle_value, giving clear contextual guidance. It does not enumerate when not to use it or name other alternatives, but the workflow hint is specific and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct resource or action: VIN decoding, vehicle valuation, repair cost estimates, editorial guides, and discovery lists are clearly separated. get_repair_cost_estimate and get_repair_cost_guide are slightly overlapping since both deal with repair pricing, but their descriptions clarify the estimate-vs-editorial-guide distinction.
All tool names follow a consistent verb_noun snake_case pattern: decode_vin, estimate_vehicle_value, get_repair_cost_estimate, get_repair_cost_guide, list_makes_models, list_repair_guides, list_repair_types. The naming is predictable and groups related operations clearly.
Seven tools is well-scoped for a car repair cost estimation server. Each tool earns its place: three discovery tools, two repair-cost tools, one VIN decoder, and one vehicle value estimator cover the domain without unnecessary bloat.
The tool surface covers the core workflows: discovering supported makes/models and repair types, decoding VINs, estimating vehicle value, getting repair cost estimates, and retrieving detailed editorial guides. There are no obvious dead ends, and the domain is read-only so CRUD-style gaps do not apply.