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Server Quality Checklist

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  • Latest release: v1.1.0

  • Disambiguation5/5

    Each tool has a clearly distinct role: fetching the spec, fetching examples, validating XML, creating a PPTX, and creating from a template. No two tools overlap in purpose, so agents should not confuse them.

    Naming Consistency2/5

    Tool names are inconsistent: three use kebab-case (get-pom-guide, get-slide-example, validate-pom-slide) while two use snake_case (create_powerpoint, create_powerpoint_from_template). This mixed convention makes the API surface feel disjointed and harder to predict.

    Tool Count5/5

    With exactly five tools, the server is well-scoped for PowerPoint generation. Each tool serves a necessary step in the workflow (guide, example, validate, create, template-create) without excess or bloat.

    Completeness5/5

    The tool surface covers the full creation lifecycle: acquiring the POM specification, obtaining sample XML, validating user-authored XML, and generating the final .pptx (both from scratch and from a template). There are no obvious missing operations for the stated domain.

  • Average 3.8/5 across 5 of 5 tools scored.

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

    • No community issues in the last 6 months
    • 1 commit in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available
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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

  • Behavior2/5

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

    No annotations are provided, so the description carries the full burden. It only states the input (POM XML) and output (.pptx file), with no disclosure of side effects, error handling, return values, or permissions. This is minimal guidance for a mutation tool.

    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 a single, focused sentence that front-loads the priority use case and conveys the core function. There is no redundant information, making it highly concise and well-structured.

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

    Completeness2/5

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

    Without annotations or an output schema, the description should explain return values or behavior, but it does not. It also does not mention related tools like get-pom-guide or validate-pom-slide. For a file-generation tool with four parameters, more detail is needed for full contextual completeness.

    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%, with detailed descriptions and examples for all four parameters. The description itself adds no extra meaning beyond the schema, so it remains at the baseline of 3.

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

    Purpose4/5

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

    The description clearly states the tool generates a .pptx file from POM-format XML, identifying the specific verb ('generate') and resource ('PowerPoint file'). However, it does not explicitly distinguish this from the sibling tool create_powerpoint_from_template, so it does not fully earn a 5.

    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?

    The description explicitly says '【最優先で使用】' (use with highest priority) and 'when the user requests creation of a PowerPoint file', giving clear when-to-use context. It does not mention exclusions or alternatives, so it misses the top score.

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

  • Behavior2/5

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

    No annotations are provided, so the description carries the full burden. It discloses that the template's background is inherited and new slides are generated, but omits other important behaviors such as whether existing files are overwritten, how the XML is validated, or what the return value is. For a file-creation tool with no annotations, this is insufficient.

    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 a single, front-loaded sentence that immediately communicates the usage context and core behavior. Every clause earns its place with no unnecessary filler.

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

    Completeness2/5

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

    Despite having 5 parameters, no annotations, and no output schema, the description is only one sentence. It covers the main purpose but lacks details about expected output, error handling, file overwrite behavior, or validation requirements. This is incomplete for a tool of this complexity.

    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 coverage is 100%, so the baseline is 3. The description adds a small amount of meaning by explaining that templatePath's background is inherited, but this is already stated in the schema's parameter description. Thus the description contributes no significant semantic value beyond the schema.

    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 tool creates a PowerPoint from an existing template, inheriting the template's background. The verb 'create...from_template' and the specific mention of template usage distinguish it from the sibling create_powerpoint tool.

    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?

    The description begins with '【テンプレート使用時】' meaning 'when using a template', explicitly indicating when this tool is appropriate. It does not mention exclusions or name the alternative create_powerpoint, but the context is clear enough for an agent to choose between the two.

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

  • Behavior2/5

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

    No annotations are provided, so the description carries the full burden. It discloses the core behavior (syntax checking) but does not mention side effects, return values, or error handling. As a validation tool, it likely has no destructive side effects, but this is not explicitly stated, leaving a gap in transparency.

    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 a single focused sentence that conveys the tool's optional nature, the timing, and the purpose. It is front-loaded with the optional marker and successfully communicates the value without unnecessary words.

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

    Completeness3/5

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

    Given the simplicity (1 parameter, no annotations, no output schema), the description covers the essential context of when to use it, but it does not explain what the tool returns or how the validation result is communicated. This is a noticeable gap for a validation tool, though the simplicity of the tool mitigates the severity.

    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%, and the parameter 'xml' is well-described in the schema as 'POM形式のXML文字列'. The tool description adds no additional parameter semantics beyond what the schema already provides, so the baseline of 3 applies.

    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 tool validates POM-format XML for syntax errors, specifying both the resource (POM XML) and the action (check). It distinguishes itself from sibling tools like create_powerpoint and get-pom-guide by focusing on validation before PowerPoint generation.

    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?

    The description explicitly states when to use the tool: after creating POM XML and before generating PowerPoint. This provides clear contextual usage. It does not name alternatives but the timing guidance makes the intended workflow evident.

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

  • Behavior3/5

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

    No annotations are provided, so the description carries the burden. It discloses that the XML is working and directly usable with create_powerpoint, but does not explicitly state whether the operation is read-only or has side effects, though '取得します' implies retrieval.

    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?

    Three concise sentences, front-loaded with the main purpose, followed by useful integration context and a list of supported types. No redundant or irrelevant content.

    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?

    For a simple one-parameter getter with no output schema, the description provides enough context: what it does, what types are supported, and how the result is used. It doesn't detail XML structure, but that's not necessary given the 'pass to create_powerpoint' hint. Could mention error behavior for invalid slide_type, but enum constraints mitigate that.

    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 covers 100% of the parameter with a detailed description and enum. The tool description simply repeats the available slide types in plain language, adding no extra meaning beyond what the schema already provides. Baseline of 3 applies.

    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 it retrieves sample XML for specific slide types, with a specific verb ('取得します') and resource (slide XML). It also mentions integration with create_powerpoint, distinguishing its purpose from sibling tools like validate-pom-slide and create_powerpoint.

    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?

    Provides clear context: use when you need a working sample XML to pass to create_powerpoint. It lists available slide types, but doesn't explicitly mention when not to use it or name alternative sibling tools.

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

  • Behavior4/5

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

    With no annotations, the description must convey behavior, and it does by describing the tool as a retrieval action ('取得します') of the POM specification. It also enumerates the exact content returned (node types, properties, layout methods), making the read-only, informational nature clear.

    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 compact and front-loaded with the mandatory action. It lists the covered node types in a single parenthetical and includes only relevant instruction and content 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 0-parameter guide-retrieval tool with no output schema, the description is complete: it specifies when to run it, what the guide contains, and its relationship to create_powerpoint. An agent has enough context to select and invoke it correctly.

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

    Parameters4/5

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

    The tool has zero parameters and an empty properties schema, so there are no parameter details to document. The 0-param baseline of 4 applies, and the description appropriately focuses on content rather than parameter semantics.

    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 states a clear action ('取得します') and a specific resource: the POM format specification along with node types, properties, and layout methods. It also ties the tool to the create_powerpoint workflow, which distinguishes it from sibling tools like get-slide-example and validate-pom-slide.

    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?

    The description explicitly instructs when to use the tool: 'PowerPointスライドを作成する前に必ず実行してください' and 'create_powerpointツールを使用する前に'. This is clear contextual guidance, though it does not mention exclusions or alternative tools for other use cases.

    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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  • Evaluate tool definition quality.

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