xpay✦ DevTools Collection

generate_plantuml_diagram

Generate a PlantUML diagram with automatic syntax validation and error reporting for auto-fix workflows. Returns embeddable image URLs for valid diagrams or structured error details for invalid syntax that can be automatically corrected. Optionally saves the diagram to a local file.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`format`	No	Output image format (SVG or PNG)	svg
`output_path`	No	Optional. Path to save diagram locally. Automatically creates all necessary parent directories. Restricted to current working directory by default. Set PLANTUML_ALLOWED_DIRS env var (colon-separated paths, or "*" for unrestricted) to allow additional directories. Only .svg and .png extensions permitted.
`plantuml_code`	Yes	PlantUML diagram code. Will be automatically validated for syntax errors before generating the diagram URL.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedMar 15, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Despite having no annotations, the description discloses key behaviors: automatic syntax validation, return of embeddable URLs or structured errors, and optional local file saving. It doesn't detail side effects like overwriting files or permission requirements, but it covers the main behavioral traits.

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?

Two sentences, no filler, front-loaded with the main action and key differentiator.

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?

With a moderate number of parameters and no output schema, the description explains the return types (URLs or error details) and optional side effect (file saving). It's sufficient for an agent to understand inputs and outputs.

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?

Input schema covers 100% of parameters with descriptions, so baseline is 3. The description adds no significant parameter details beyond the schema, though it reiterates the auto-validation behavior for plantuml_code.

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 uses a specific verb ('Generate') and resource ('PlantUML diagram') and clearly distinguishes from sibling tools like decode_plantuml/encode_plantuml by adding automatic syntax validation and error reporting.

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?

States the tool is for 'auto-fix workflows' and describes its typical use of generating diagrams with validation. It doesn't explicitly name alternatives, but the description implies when to use it versus other PlantUML utilities.

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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TDQS

C2.4/5.0

Disambiguation2/5

Several tools have overlapping or ambiguous purposes that could confuse an agent. For example, analyze_code, analyze_patterns, and analyze_design_patterns all involve code analysis with unclear boundaries, while check_deceptive_patterns and check_placeholders seem like subsets of analyze_code. The NPM tools form a coherent group but are distinct from the rest, creating a fragmented toolset.

Naming Consistency2/5

Naming conventions are highly inconsistent across the toolset. Some tools use snake_case (e.g., analyze_code, execute_code), others use camelCase (e.g., npmAlternatives, npmChangelogAnalysis), and there are mixed styles like query-docs with hyphens. The NPM tools follow a consistent npmPrefix pattern internally, but this is not applied to other tools, leading to overall chaos.

Tool Count2/5

With 39 tools, this server is overloaded for a 'DevTools Collection' scope. The count feels excessive, as many tools could be consolidated (e.g., multiple analysis tools) or logically grouped. While the NPM tools are numerous but focused, the overall set lacks cohesion, making it cumbersome for an agent to navigate and select appropriate tools efficiently.

Completeness3/5

The toolset covers a broad range of development tasks, including code analysis, execution, documentation, and package management, but there are notable gaps. For example, there is no tool for code generation or refactoring, and the Microsoft and NPM tools are well-covered but isolated from other functionalities. The surface is extensive but not fully integrated, with some dead ends in workflow transitions.

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