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Generate Uml Diagram Tool

generate-uml-diagram

Use this when the user supplies source code and asks for UML, Mermaid, sequence, class, component, or architecture diagrams. After authorization, this state-changing generation consumes AI credits, creates a generation, and can save markdown to a Space. Public Spaces expose saved diagrams. Use browser guidance for local uploads or full-repository diagrams.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoOptional generation name.
filenameYesFilename for the source code.
source_codeYesSource code to analyze.
diagram_typeYesClass Diagrams, Sequence Diagrams, Use Case Diagrams, Activity Diagrams, Component Diagrams, State Diagrams, or Object Diagrams.
save_to_spaceNoOptional destination Space item.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Goes well beyond the annotations by disclosing that it consumes AI credits, requires authorization, creates a generation, and can persist markdown to a Space with public exposure implications. This is valuable cost/side-effect context for a write tool, though reversibility and rate limits are not stated.

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

Conciseness4/5

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

Three front-loaded sentences: trigger, behavioral consequences, and a boundary note. Dense with little waste, though the final sentence ('Use browser guidance...') is under-specified for the space it occupies.

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

Completeness4/5

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

No output schema exists, yet the description covers trigger, cost, side effects, and persistence/sharing outcomes. A complex nested-parameter mutation tool would benefit from naming related read tools like get-generation or list-generators, but the essentials are present.

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?

Schema description coverage is 100%, so the schema already documents all five parameters including the nested save_to_space object. The description adds only marginal mapping ('markdown to a Space' for save_to_space) and no format or constraint detail beyond the schema, so the baseline 3 holds.

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?

States a specific verb (generate) plus resource (UML diagram) and enumerates the diagram flavors (Mermaid, sequence, class, component, architecture) it covers. An agent can distinguish this from the many sibling generate-* tools (documentation, tests, comments) without opening a schema.

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

Usage Guidelines4/5

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

Gives a clear trigger condition: the user supplies source code and asks for UML/diagram output. It also points elsewhere for out-of-scope cases ('browser guidance for local uploads or full-repository diagrams'), though that reference is vague and no sibling generator is named for direct comparison.

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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