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chelsea-zhou

AIE7-MCP

by chelsea-zhou
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Server Quality Checklist

58%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool addresses a completely different use case—web search, dice rolling, and holiday lookup—so there is no overlap or confusion between them.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (web_search, roll_dice, check_holiday), making the API predictable and easy to navigate.

    Tool Count4/5

    With 3 tools, the set is lean but not unreasonably so; however, the tools are unrelated, so the overall scope feels somewhat scattered rather than cohesive, which is why it's not a perfect 5.

    Completeness3/5

    The server lacks a clear domain, so completeness is hard to evaluate; while each tool is self-contained, there is no broader workflow that reveals obvious gaps, but also no evidence of comprehensive coverage of a unified purpose.

  • Average 3.4/5 across 3 of 3 tools scored. Lowest: 2.7/5.

    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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  • This repository includes a README.md file.

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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 must carry the burden of behavioral disclosure. It only states 'roll the dice' without explaining what this entails: it does not mention that the outcome is random, what format the notation should take, or whether there are any side effects or outputs beyond what the output schema defines. The behavioral trait of randomness is implied but 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.

    Conciseness3/5

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

    The description is a single, terse sentence with no redundancy. However, it is under-specified: it lacks necessary details such as the notation format and the purpose of num_rolls. While concise, it sacrifices essential information, making it only minimally adequate.

    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 two parameters and the absence of annotations, the description is incomplete. It does not explain the notation format or the num_rolls parameter, both of which are essential for effective use. The presence of an output schema helps with return values, but the tool's core behavior and parameter semantics remain unexplained.

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

    Parameters1/5

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

    Schema description coverage is 0%, so the description must compensate for both parameters. It only mentions 'notation' as a concept but does not define its syntax (e.g., '2d6'), and it entirely omits the 'num_rolls' parameter. The description provides almost no added meaning beyond the schema's bare field names.

    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 'Roll the dice with the given notation' clearly states the action (roll) and the resource (dice), with a modifier ('with the given notation') that ties to the primary parameter. It is specific enough to distinguish from siblings (web_search, check_holiday), which are entirely unrelated actions.

    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?

    No guidance is provided about when to use this tool versus alternatives. The description does not mention any context, prerequisites, or exclusions. Siblings are unrelated but there is no explicit 'use this when' direction, leaving the agent to infer from the name 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?

    No annotations are provided, so the description alone must disclose behavioral traits. It only states the basic action without mentioning important aspects like result format, rate limits, authentication, or internet dependency. This leaves the agent without critical behavioral context.

    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 with no redundant information. It gets straight to the point and every word serves a purpose.

    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?

    The tool is simple, but with no annotations and no usage context, the description is minimal. It defines the core action but omits any guidance on when to use it or what to expect behaviorally. The presence of an output schema covers return values, but other context is thin.

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

    Parameters2/5

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

    With 0% schema_description_coverage, the description needed to enrich the parameter meaning. However, it merely says 'given query', which only restates the parameter name and adds no additional semantics like expected format or search options. It fails to compensate for the sparse 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's function with a specific verb 'Search' and resource 'the web', and specifies the input as 'given query'. It inherently distinguishes itself from the unrelated sibling tools roll_dice and check_holiday.

    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 implies when to use this tool: when web information is needed for a query. Although it doesn't explicitly name alternatives or exclusions, the sibling tools are so different that the usage context is clear. It lacks explicit guidance on preferences or limitations.

    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 full burden for behavioral disclosure. It only states the basic action and format, but does not mention what the tool returns, how it handles invalid inputs, or any limitations. This is a significant 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 concise and front-loaded with the purpose. The additional format information is compact and earned, with no redundant or filler 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?

    Given the tool's simplicity and the presence of an output schema, the description provides sufficient invocation details (date format and country code). It lacks broader usage context, but the output schema covers return value details, making the description adequately complete for this low-complexity tool.

    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 input schema has 0% description coverage, so the description must add parameter meaning. It does so by specifying the date format (YYYY-MM-DD) and giving country code examples (US, CA, GB), which provides essential context beyond the bare schema fields. It is not exhaustive but meaningfully compensates for the schema gap.

    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's purpose: 'Get holiday information for a specific date and country.' It uses a specific verb and resource, and the date/country scope differentiates it from the unrelated siblings web_search and roll_dice.

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

    Usage Guidelines3/5

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

    Usage is implied from the purpose (use for holiday information), but there is no explicit guidance on when to use this tool versus alternatives or any exclusions. The format hints (date format, country code) provide some usage direction, but not enough to warrant a higher score.

    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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