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eisuke000111

AWS Customer Playbook Advisor MCP

by eisuke000111
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Server Quality Checklist

58%
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  • Latest release: v1.0.0

  • Disambiguation3/5

    The tools have some overlap in purpose, as all three retrieve AWS security playbooks or guidance, making them potentially confusing. However, descriptions help differentiate them: get_aws_playbook fetches a specific playbook, get_prevention_guidance focuses on preventive guidance, and list_available_playbooks lists available options. This reduces ambiguity but doesn't eliminate it entirely.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern using snake_case: get_aws_playbook, get_prevention_guidance, and list_available_playbooks. The verbs 'get' and 'list' are clear and predictable, with no deviations in style or convention across the set.

    Tool Count3/5

    With only 3 tools, the count feels thin for a server focused on AWS security playbooks, as it may lack operations like creating, updating, or deleting playbooks. However, it's reasonable for a read-only advisory service, though it borders on being under-scoped for typical agent workflows.

    Completeness2/5

    The tool surface is significantly incomplete for the domain of AWS security playbook management. It only supports retrieval and listing operations, with no tools for creating, updating, or applying playbooks. This will likely cause agent failures when trying to perform full lifecycle management, leaving obvious gaps in coverage.

  • Average 3/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 0 commits 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?

    With no annotations provided, the description carries full burden but provides minimal behavioral context. It mentions retrieving 'latest' playbooks which implies freshness, but doesn't disclose authentication requirements, rate limits, error conditions, response format, or whether this is a read-only operation. For a tool with no annotation coverage, 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, efficient Japanese sentence that gets straight to the point with zero wasted words. It's appropriately sized for the tool's apparent complexity and front-loads the core functionality.

    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?

    For a tool with no annotations and no output schema, the description is incomplete. It doesn't explain what format the playbooks are returned in, whether there's pagination, error handling, or authentication requirements. Given the security context and lack of structured metadata, more behavioral disclosure would be expected.

    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 description doesn't add any parameter information beyond what's already in the schema (which has 100% coverage). It doesn't explain the relationship between 'scenario' and 'playbook_name', provide additional examples, or clarify edge cases. With complete schema coverage, the baseline of 3 is appropriate.

    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 action ('取得します' - retrieves) and resource ('AWS公式プレイブックフレームワークから最新のセキュリティプレイブック' - latest security playbooks from AWS official playbook framework). It distinguishes from 'list_available_playbooks' by specifying retrieval of actual content rather than listing, but doesn't explicitly differentiate from 'get_prevention_guidance' which might provide different types of guidance.

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

    Usage Guidelines2/5

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

    The description provides no guidance on when to use this tool versus the sibling tools 'get_prevention_guidance' or 'list_available_playbooks'. It doesn't specify prerequisites, constraints, or alternative scenarios where other tools would be more appropriate.

    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 of behavioral disclosure. It states the tool retrieves guidance from official playbooks, implying a read-only operation, but doesn't cover critical aspects like authentication requirements, rate limits, error handling, or response format. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

    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, efficient sentence in Japanese that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.

    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?

    Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., guidance format, structure, or examples), nor does it address behavioral traits like authentication or error handling. For a tool with no structured metadata, the description should provide more context to be fully helpful.

    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 description doesn't add any parameter-specific information beyond what's in the input schema, which has 100% coverage with clear descriptions for both parameters ('service' and optional 'question'). Since schema coverage is high, the baseline score is 3, as the description doesn't compensate but also doesn't detract from the schema's documentation.

    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's purpose: '取得します' (retrieves) '予防的セキュリティガイダンス' (preventive security guidance) from '公式プレイブック' (official playbooks) for AWS services. It specifies the resource (AWS preventive security guidance) and source (official playbooks), though it doesn't explicitly differentiate from sibling tools like 'get_aws_playbook' or 'list_available_playbooks' beyond mentioning 'preventive' guidance.

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

    Usage Guidelines2/5

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

    The description provides no guidance on when to use this tool versus its siblings ('get_aws_playbook', 'list_available_playbooks'). It doesn't specify use cases, prerequisites, or exclusions, leaving the agent to infer usage from the tool name and description alone.

    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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It only states what the tool does (retrieves a list) without mentioning any behavioral traits such as permissions needed, rate limits, pagination, or response format. This is inadequate for a tool with zero annotation coverage.

    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, efficient sentence in Japanese that directly states the tool's purpose without any unnecessary words or fluff. It is appropriately sized and front-loaded, making it easy to parse quickly.

    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?

    Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the returned list contains (e.g., format, structure, or fields), behavioral aspects like safety or side effects, or how it differs from siblings. For a tool with no structured data support, this leaves significant gaps.

    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 0 parameters, and the schema description coverage is 100% (as there are no parameters to describe). The description doesn't need to add parameter semantics, so a baseline score of 4 is appropriate, as it doesn't introduce confusion or redundancy.

    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 verb ('取得します' - get/retrieve) and resource ('AWSセキュリティプレイブックの一覧' - list of AWS security playbooks), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_aws_playbook' or 'get_prevention_guidance', which prevents a perfect score.

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

    Usage Guidelines2/5

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

    The description provides no guidance on when to use this tool versus the sibling tools 'get_aws_playbook' or 'get_prevention_guidance'. It lacks any context about alternatives, prerequisites, or exclusions, leaving the agent to infer usage from tool names alone.

    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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