find_engineering_unitFind the official UNECE Rec. 20 engineering unit symbol for a given description. ALWAYS call this before using any engineering unit — NEVER guess unit symbols.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Description or common name of the unit (e.g. "revolutions per minute", "celsius", "pressure bar") |
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so the safety profile is covered. The description adds the authoritative standard ('UNECE Rec. 20') and a usage policy, but does not disclose details such as return shape, exact-match versus fuzzy-match behavior, or what happens when no symbol is found.
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 short sentences with no filler, and the core purpose appears first. The imperative rule is front-loaded where it matters and 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, idempotent lookup, the description covers purpose, input, and mandatory usage well. The main gap is the lack of any note about the response representation or no-match behavior, but the low complexity and existing annotations keep this from being a significant deficiency.
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?
The single 'query' parameter is fully documented in the schema with a clear description and examples. The tool description only refers to it as 'a given description', adding no significant meaning beyond the schema.
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 names a specific verb ('Find'), a precise resource ('official UNECE Rec. 20 engineering unit symbol'), and the input it operates on ('a given description'). It clearly distinguishes this tool from the sibling tools, none of which are engineering-unit lookups.
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 gives explicit when-to-use guidance: 'ALWAYS call this before using any engineering unit'. It also states a hard behavioral rule: 'NEVER guess unit symbols', which tells the agent the alternative to avoid. No sibling tool is an alternative, so no further routing is needed.
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 targets a distinct resource or operation: unit lookup, reusable-block lookup, DSL reference, type details, namespaces, type listing/search, and the four model operations are all clearly separated. Even the two search-like tools (find_reusable_block and search_types) have different intents and return different kinds of results, so an agent should not misselect.
Most utility tools follow a verb_first_snake_case pattern (find_*, get_*, list_*, search_*, resolve_*), but the four workflow tools use an opcua_model_* prefix (create, generate, reverse, validate). This is a blend of two systematic conventions rather than chaotic naming, but it is not fully uniform.
Twelve tools is well within the ideal range for this domain, and each tool covers a distinct aspect of the modeling workflow from discovery and dependency resolution to validation and artifact generation. No tool feels redundant, and the count is appropriate for the stated purpose.
The tool surface covers the full lifecycle: discovering namespaces/types/units/reusable blocks, resolving dependencies, authoring YAML, validating it, generating artifacts, and reverse-engineering existing NodeSet files. There are no obvious dead ends or essential missing operations for the OPC UA modeling workflow.