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achmadya-dev

drawio

by achmadya-dev
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.3.2

  • Disambiguation5/5

    The two tools have completely distinct purposes: one searches the shape library, the other creates and displays diagrams. There is no functional overlap or ambiguity.

    Naming Consistency5/5

    Both tool names follow a consistent verb_noun pattern in snake_case (search_shapes, show_inline_drawio), making them predictable and easy to differentiate.

    Tool Count4/5

    With only 2 tools, the server is minimal but well-scoped for its core function of creating draw.io diagrams. Each tool serves a clear, necessary purpose, and adding more would risk bloat.

    Completeness4/5

    The server covers the essential workflow: searching for industry-specific shapes and generating diagrams in both XML and Mermaid formats. Minor gaps like diagram editing or listing tools are outside its intended scope.

  • Average 4.8/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 12 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • This repository is licensed under Apache 2.0.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior4/5

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

    No annotations are provided, so the description carries full burden. It discloses the output content and how to use the style strings directly, implying a read-only search operation. However, it does not explicitly state whether the tool has side effects (though it is clearly a search), which would add clarity.

    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?

    The description is front-loaded with the core purpose, and each sentence adds value. It could be slightly more concise by removing the last conditional ('Also skip if...') but overall it is well-structured and informative without being verbose.

    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?

    Given the absence of an output schema, the description fully explains the return values (style strings, dimensions, titles) and their usage. For a search tool with two well-documented parameters, the description provides complete context for an AI agent to select and invoke the tool correctly.

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

    Parameters5/5

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

    Both parameters have detailed descriptions in the schema (100% coverage). The description adds concrete examples for the query parameter ('pid globe valve', etc.) and specifies default and max for limit, going beyond the schema to enhance understanding.

    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 states the specific verb ('Search') and resource ('draw.io shape library'), and describes the outputs ('exact style strings, dimensions, and titles'). It effectively distinguishes from the only sibling tool, create_diagram, by specifying its unique purpose for industry-specific icons.

    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 explicitly states when to use ('diagrams that need industry-specific or branded icons') and when not to use ('standard diagram types...'). It provides clear exclusion criteria and references alternatives ('basic geometric shapes covered in the XML reference').

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior5/5

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

    The description adds substantial behavioral context beyond the annotations, such as the effect of creating a diagram, the mutual exclusivity of parameters, and the impact of `postLayout` and `routing`. It does not contradict the annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint).

    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?

    The description is well-structured with sections, bullet points, and headers, and it front-loads key information. However, it is quite lengthy and includes detailed references (e.g., dark mode colors, metadata) that might be considered excessive for a tool description, slightly reducing conciseness.

    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 complex tool that creates diagrams from two input formats, the description is exceptionally complete. It covers format selection, extensive references for both Mermaid and XML, edge routing, containers, layers, tags, metadata, dark mode, and layout options. The schema covers all parameters, and the description fully compensates for the lack of an output schema by explaining the tool's behavior and results.

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

    Parameters5/5

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

    Schema coverage is 100%, but the description adds extensive semantics for each parameter, including format selection rules, when to use each option, and detailed interaction effects (e.g., `postLayout` vs `routing`). This goes far beyond the schema definitions.

    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 states that the tool creates and displays an interactive draw.io diagram. It explains the two input formats (XML and Mermaid) and provides extensive guidance on when to use each, effectively distinguishing the tool from its sibling `search_shapes`.

    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 provides explicit when-to-use and when-not-to-use guidance, including a detailed list of diagram types suitable for Mermaid vs XML, a user preference override section, and when to call the sibling tool `search_shapes`. This leaves no ambiguity about appropriate usage.

    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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