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CalWtr

relative-interpreter-mcp

by CalWtr

Get model

get_model

Retrieve a compact outline of a model's structure, including nodes, links, views, and validation findings. Submodels appear summarized to keep the overview clear and expandable.

Instructions

The current scope as a compact outline: nodes with their kind and value, links as arrows between named ports, views, and validation findings. Submodels are summarised, not expanded — use enter_submodel or get_element to look inside one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelIdNoDefaults to the selected model.
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses that the output is a 'compact outline' and that submodels are not expanded—useful behavioral context. It does not explicitly state whether the operation is read-only, but the 'get' verb and the nature of the output strongly imply it. It adds meaningful detail beyond the title.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the output summary and then a clear limitation and alternative. Every sentence provides needed information with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read tool with one optional parameter, the description fully covers the return content (nodes, links, views, validation findings) and key behavior (submodel summarization). No output schema exists, so the description adequately explains what the caller will receive. Sibling tools provide context for navigation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has one parameter (modelId) with 100% coverage: 'Defaults to the selected model.' The description does not add additional parameter meaning beyond what the schema provides, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly explains what the tool returns: 'The current scope as a compact outline: nodes with their kind and value, links as arrows between named ports, views, and validation findings.' It also distinguishes itself from sibling tools by noting that submodels are summarized, not expanded, and points to enter_submodel/get_element for that purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit when-not guidance: submodels are summarized, so to look inside one, use enter_submodel or get_element. It also implies this tool is for getting an overview of the current scope, which is clear from context and sibling tools.

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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