Validate a part number and check whether it exists in the PartsTable catalog (16M+ parts from government, OEM, and commercial authority sources). Returns structural validity and catalog existence.
| Name | Required | Description | Default |
|---|---|---|---|
| partNumber | Yes | The part number to validate |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description states the tool returns structural validity and catalog existence, which is transparent about the two aspects of the result. However, it does not disclose side effects (likely none, but unstated), authentication requirements, rate limits, or whether the validation is case-sensitive or supports wildcards. It adequately conveys the core behavioral traits but leaves some details unspecified.
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 two sentences, front-loaded with the core action and followed by a concise result summary. Every sentence adds value, with no wasted words. It fits the standard pattern for effective tool descriptions.
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 only one simple parameter and no output schema, the description does enough by explaining the tool's purpose and result structure. However, it would benefit from briefly noting whether the tool is purely a read operation (likely) and what happens for invalid formats (e.g., error vs. false). Still, it provides sufficient context for the agent to use correctly given the tool's simplicity.
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%, meaning the schema already documents 'partNumber'. The description adds meaning beyond the schema by specifying that validation includes both structural checks and catalog existence against a large, multi-source database. This supplementary context helps the agent understand the part number matters and what type of lookup is performed, earning a score above the baseline of 3.
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 ('Validate') and resource ('part number'), clearly states the action of checking existence in the PartsTable catalog, and provides context about the catalog's scope (16M+ parts from multiple authority sources). The result dimensions ('structural validity and catalog existence') are explicitly named. This distinguishes it from siblings like 'get-part' (retrieval) and 'normalize-pn' (format conversion).
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 implies use for checking if a part number is valid and exists in the catalog. It does not explicitly state when not to use it or name alternatives (e.g., 'search-parts' for fuzzy lookups, 'normalize-pn' for format cleaning). However, given the single parameter and clear two-dimensional output, the context of use is sufficiently clear for the agent. A small loss for missing explicit when-not guidance.
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 has a clearly distinct purpose: retrieving a single part record, finding substitutes, normalizing part numbers, batch searching, and validating existence. There is no overlap or ambiguity.
All tool names follow a consistent verb_noun pattern (e.g., get-part, normalize-pn, validate-pn) using snake_case. The naming is predictable and easy to understand.
With 5 tools, the server is well-scoped for a read-only parts catalog. Each tool serves a essential function without being too few or overly numerous.
The tool set covers the core operations needed for a parts table: record retrieval, cross-reference lookup, normalization, batch existence check, and validation. There are no obvious gaps given the read-only design.
