Check current prices and stock levels for Dicker Data product codes to inform purchasing decisions.
Look up live pricing and stock-on-hand for one or more Dicker Data product codes (part numbers).
| Name | Required | Description | Default |
|---|---|---|---|
| productCodes | Yes | One or more Dicker Data product/part numbers to price and check stock for. |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. 'Look up live pricing and stock-on-hand' makes the read-only nature and freshness of data reasonably clear, but it does not describe output structure, error behavior, or limits on the number of product codes.
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?
The description is a single, front-loaded sentence with no filler. Every phrase contributes meaning, and it is immediately clear what the tool does.
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 simple one-parameter lookup tool, the description is largely complete: it names the input type and the two key output aspects (pricing and stock). Minor gaps such as maximum number of codes or response format are not critical for this level of complexity.
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 the schema already documents the single parameter. The description only restates that one or more product codes are accepted and adds little meaning beyond the schema's own description.
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 uses a specific verb ('Look up') and names the resource ('live pricing and stock-on-hand for Dicker Data product codes'). It is clear and hints at differentiation from dickerdata_get_price by including stock-on-hand and supporting multiple codes, but it does not explicitly distinguish itself from that sibling.
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?
No guidance is given about when to use this tool versus dickerdata_get_price or other siblings. There are no explicit conditions, prerequisites, or exclusions, so an agent must infer the appropriate use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.