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gargoyle92
by gargoyle92

Server Quality Checklist

67%
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  • Latest release: v0.0.10

  • Disambiguation5/5

    Each tool has a distinct role: auto-task-tracker for automatic monitoring, task-started for initiating, and task-completed for finishing. No overlap.

    Naming Consistency4/5

    All names use hyphens and are descriptive, but 'auto-task-tracker' is a noun phrase while 'task-started' and 'task-completed' are verb phrases, slightly inconsistent.

    Tool Count4/5

    3 tools is minimal but reasonable for a simple task tracking server, covering the basic lifecycle without being too sparse.

    Completeness4/5

    Covers start, auto-tracking, and end. Missing manual progress updates or error states, but sufficient for basic automation.

  • Average 3.8/5 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
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

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How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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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 fully convey behavioral traits. It only states when to call the tool, with no details on side effects, idempotency, or what happens after invocation. This is insufficient for an agent to understand the tool's behavior fully.

    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, concise sentence that is front-loaded with the key action. It earns its place with no waste, though it could be slightly more structured.

    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 low complexity (one required parameter, no output schema), the description is adequate for understanding when to use the tool and what input is needed. It does not cover return values, but that is acceptable without an output schema.

    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 input schema has 100% coverage for the single parameter 'taskDescription', with a clear schema description. The tool description adds no additional meaning beyond the schema, so a baseline score 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: 'Call this when you start any task, answer a question, or start work.' It effectively communicates the tool's purpose but does not provide explicit differentiation from siblings like 'auto-task-tracker' or 'task-completed'.

    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 description gives clear usage context ('when you start any task, answer a question, or start work'), but it lacks any when-not-to-use guidance or mention of alternatives, such as 'auto-task-tracker' for automated tracking.

    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 full burden for behavioral disclosure. It indicates this is a logging/tracking action (non-destructive), but does not state any side effects, permission requirements, or behavior if called multiple times. Adequate but could be more transparent about what 'tracks your activity' means.

    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 concise sentences that front-load the primary purpose. Every word is useful with no redundancy. Excellent structure.

    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 simplicity of the tool (3 params, no output schema), the description covers the essential context: when to call and what it does. It could mention the relationship with sibling tools (e.g., 'use task-started to begin a task') but is otherwise complete.

    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%, meaning all parameters are described in the input schema. The description does not add any additional meaning beyond what the schema already provides (e.g., enum values or field purposes). Baseline score 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?

    Description clearly states the tool is for reporting completion of tasks, answering questions, or finishing work. It uses a specific verb ('call this when you finish') and resource ('task completion tracking'). However, it does not explicitly distinguish from sibling tools like 'task-started' or 'auto-task-tracker', which slightly reduces clarity.

    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?

    Description provides clear context on when to use: 'when you finish any task, answer a question, or complete work.' It implies this is for manual completion logging. Missing explicit guidance on when not to use or differentiation from siblings, but the intent is clear enough for an agent.

    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 fully bears the burden of disclosure. It reveals automatic self-triggering every 10 seconds and the conditions for that. It does not detail side effects or interactions with other tools, but for a simple monitoring tool, this is sufficient.

    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, with the purpose as the first sentence, followed by trigger conditions. Every sentence adds value without unnecessary words.

    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 tool with one optional parameter and no output schema, the description covers purpose, trigger conditions, and parameter meaning. It is complete enough for an agent to understand when and how to invoke it, though it lacks details on return values or progress format.

    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% with one parameter 'taskThresholdSeconds' described as 'Auto-trigger when task exceeds this duration'. The description reinforces this with the default value of 30 seconds but adds no new semantics beyond what the schema provides.

    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 automatically monitors task progress during long-running operations and updates progress without user prompting. It distinguishes from sibling tools 'task-completed' and 'task-started' by emphasizing automation.

    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 specifies conditions for automatic triggering (tasks >30s, multiple tools, complex processing), implying when to use this tool over manual alternatives. However, it does not explicitly state when not to use it or name alternatives, leaving some room for interpretation.

    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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