get_dsl_referenceGet the grammar reference for the OPC UA modeler YAML DSL: file header, top-level sections, name-prefix conventions, minimal examples, and common mistakes. Call this FIRST before writing any YAML model by hand. Works without an API key.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and open-world hints, so the safety profile is covered. The description adds useful context beyond annotations: it lists the content areas of the reference and states that no API key is required. This is appropriate for a no-parameter reference lookup.
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 with no filler. The first sentence front-loads what the tool returns, and the second delivers the usage instruction and auth note. Every clause 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 no-parameter, no-output-schema reference tool, the description is complete: it states the content scope, the recommended invocation point, and auth requirements. Combined with the annotations, an agent has everything needed to select and call this tool correctly.
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 tool has zero parameters, so the description does not need to explain parameter semantics. The schema coverage is 100% vacuously; baseline 4 applies. No additional parameter meaning is required.
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 ('Get') with a specific resource ('grammar reference for the OPC UA modeler YAML DSL') and enumerates the contents (file header, sections, naming conventions, examples, mistakes). This clearly distinguishes it from sibling tools like get_type_details or opcua_model_create, which address different resources.
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?
It explicitly instructs 'Call this FIRST before writing any YAML model by hand', which gives a clear condition for use. It also notes that it works without an API key, implying it is a low-friction first step. It does not name alternatives or explicit when-not-to-use cases, so it falls short of the full 5.
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.