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Server Quality Checklist

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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool addresses a clearly different temporal scope: the current week, an arbitrary week by date, and the rolling set of upcoming prescribed workouts. While get_current_week and get_week could both return the current week in some cases, their intended use cases are distinct and visible from the descriptions.

    Naming Consistency4/5

    All tools follow a get_ prefix and use temporal terms, which creates a predictable pattern. get_upcoming is slightly less noun-like than get_current_week and get_week, but the naming style is still consistent and readable.

    Tool Count5/5

    Three tools is a well-scoped size for a read-only training-plan retrieval server. Each tool serves a distinct need and none feels redundant or padding.

    Completeness4/5

    The server covers the primary retrieval needs for a training plan: current week, any specific week, and upcoming planned workouts. Minor gaps like direct workout-level detail or historical summaries are not obviously required for the stated scope.

  • Average 3.9/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 5 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
  • This repository is licensed under MIT License.

  • 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

  • Behavior5/5

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

    With no annotations, the description carries the full burden of behavioral disclosure. It does this exceptionally well: it explains the status vocabulary, warns that planned_km is the reliable number and raw distance_km may be blank on interval days, and clarifies what the coach's session vs. SisRUN-matched delivered data means.

    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 a single structured enumeration with no filler words, and all listed items are meaningful. It is slightly long and runs the items together in one sentence, so a bulleted or shorter phrasing would be improve readability without losing 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 parameterless read tool, the description is almost complete: it covers the data included, notable field quirks, and status meanings. It does not specify things like timezone, but that is a minor omission given the output schema exists and the intended meaning is clear.

    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?

    There are no parameters, so the schema covers everything needed. The description adds value by focusing on the output structure, which is appropriate given the zero-parameter context.

    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 resource by saying 'The current week's training plan' and enumerates what it contains. It is more than a tautology and distinguishes from siblings by the 'current week' qualifier, though it lacks an explicit retrieval verb and does not directly compare to siblings.

    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 does not explicitly say when to use this tool versus get_week or get_upcoming. The 'current week' phrasing implies the usage context, but there is no direct guidance about alternatives or when not to use it.

    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?

    There are no annotations, so the description carries the burden of behavioral disclosure. It explains the status filter, exclusion of past workouts, and the configurable future-week window, which are the key behavioral characteristics needed by an agent.

    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?

    A single, tight sentence covers purpose, status filter, time window, default, and max. No filler or redundant restating of the tool name.

    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 an output schema, the description provides enough information to understand what the tool returns and how the parameter behaves. It could be improved by acknowledging the sibling tools and clarifying ordering, but nothing critical is missing.

    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 only provides the type and default, but the description adds semantic meaning: weeks_ahead controls the number of future weeks beyond the current week, with a default of 1 and max of 8. This makes the parameter's effect clear.

    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 identifies a specific resource (prescribed workouts) and a specific status filter (Proposto) with a clear time window (today forward through future weeks). It does not explicitly mention sibling tools, but the 'today forward' scope differentiates it from get_current_week and get_week well enough.

    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?

    The time window implies the intended use: retrieving upcoming proposed workouts. However, it does not give explicit guidance on when to choose this over get_current_week or get_week, nor when not to use it.

    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?

    No annotations are provided, so the description carries the burden. It discloses a non-obvious behavioral trait: each week hop away from the current week costs an extra request. It does not discuss edge cases or invalid dates, but it gives the agent useful insight beyond the schema.

    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, front-loaded purpose, no filler. It states what the tool does and then adds the cost caveat efficiently.

    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?

    The tool has only one required parameter, an output schema exists, and the description covers parameter format and an important behavioral cost. It could be more complete by explicitly naming which sibling to use for current or upcoming weeks, but the essentials for invoking it correctly are present.

    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 schema only says date is a string, so the description's 'YYYY-MM-DD' format and statement that the week contains that date add critical meaning. With 0% schema coverage, the description compensates well for the tool's one parameter.

    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 returns 'the training plan for the week containing date', making the resource and action identifiable. It does not explicitly distinguish itself from get_current_week or get_upcoming, but the purpose is unambiguous.

    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?

    The cost note ('Navigating far from the current week costs one request per week hop') implies that dates far from the current week should be avoided when possible, but it never says when to use this tool rather than get_current_week or get_upcoming. The usage context is implied, not explicit.

    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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