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QoutaID

QoutaMCP

by QoutaID
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Server Quality Checklist

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  • Latest release: v1.0.0

  • Disambiguation4/5

    The tools have mostly distinct purposes: detect_stack is for quick tech stack detection, inspect_project provides a comprehensive analysis, and list_key_files focuses on categorizing key files. However, there is some overlap between detect_stack and inspect_project, as both involve analyzing project components, which could cause mild confusion about when to use each.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (detect_stack, inspect_project, list_key_files), using snake_case throughout. The verbs (detect, inspect, list) are clear and descriptive, making the naming predictable and easy to understand.

    Tool Count4/5

    With 3 tools, the count is reasonable for a project analysis server, covering key aspects like tech detection, detailed inspection, and file listing. It is slightly lean but well-scoped, as each tool serves a distinct function without unnecessary bloat, though a few more tools might enhance coverage.

    Completeness3/5

    The toolset covers analysis and listing functions well, but there are notable gaps for a project management domain. For example, it lacks tools for modifying or updating projects (e.g., add_dependency, update_config), which could limit agent workflows. The surface is functional for inspection but incomplete for broader project operations.

  • Average 3.7/5 across 3 of 3 tools scored. Lowest: 2.9/5.

    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 is passing

  • This repository is licensed under ISC 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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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 of behavioral disclosure. It mentions categorization by purpose, which adds some context, but fails to describe critical behaviors such as output format, error handling, permissions needed, or rate limits. For a tool with no annotations, this is a significant gap.

    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 that front-loads the purpose and categorization without any wasted words. It is appropriately sized for the tool's complexity and structure.

    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 does not explain what the tool returns (e.g., list format, categories), error conditions, or behavioral traits, leaving gaps for the agent to infer. This is inadequate for a tool with no structured support.

    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% description coverage, with the 'path' parameter documented as 'Path to the project directory.' The description does not add any meaning beyond this, such as format examples or constraints, so it meets the baseline of 3 where the schema does the heavy lifting.

    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: 'List key files in a project, categorized by purpose: entry points, config files, and documentation.' It specifies the verb ('List'), resource ('key files'), and scope ('in a project'), but does not explicitly differentiate from sibling tools like 'detect_stack' or 'inspect_project', which prevents a score of 5.

    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 alternatives. It lacks context about prerequisites, exclusions, or comparisons to sibling tools like 'detect_stack' and 'inspect_project', leaving the agent without clear usage direction.

    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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool returns a 'complete snapshot' but lacks details on performance (e.g., speed, resource usage), error handling, or output format. It adds some context about the analysis scope but is incomplete for a tool with no annotations.

    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 front-loaded with the core purpose and output, using two concise sentences with zero waste. Every word earns its place, making it easy for an AI agent to quickly grasp the tool's role.

    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 complexity of analyzing a project directory with no annotations and no output schema, the description is adequate but has clear gaps. It outlines what the tool does but lacks details on behavioral traits, output structure, or limitations, making it minimally viable for agent use.

    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%, so the schema fully documents all three parameters. The description does not add any meaning beyond the schema, such as explaining how 'maxDepth' affects the analysis or what 'includeHidden' might reveal. Baseline 3 is appropriate when the schema does the heavy lifting.

    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 specific action ('Analyze a project directory') and the comprehensive output ('complete snapshot including detected languages, frameworks, entry points, structure summary, and dependencies'), distinguishing it from sibling tools like 'detect_stack' and 'list_key_files' by emphasizing breadth of analysis.

    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 provides clear context as 'the primary tool for understanding a project,' implying it should be used for initial comprehensive analysis. However, it does not explicitly state when to use alternatives like 'detect_stack' or 'list_key_files,' nor does it mention exclusions or prerequisites.

    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?

    With no annotations provided, the description carries full burden for behavioral disclosure. It mentions performance characteristics ('faster and lighter') and output scope ('returns runtime, framework, database hints, and frontend info'), which adds useful context. However, it doesn't describe error handling, permission requirements, or what happens with invalid paths, leaving some behavioral aspects unclear.

    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 perfectly concise with two sentences that each earn their place: the first states the core purpose, the second provides comparative context and output details. No wasted words, front-loaded with the main action.

    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 moderate complexity (single parameter, no output schema, no annotations), the description provides good contextual coverage. It explains what the tool does, how it compares to alternatives, and what information it returns. The main gap is lack of output format details, but for a detection tool with no output schema, this is a minor limitation.

    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 one parameter clearly documented in the schema. The description doesn't add any parameter-specific information beyond what the schema provides (path to project directory). The baseline score of 3 is appropriate when the schema does the heavy lifting for parameter documentation.

    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 specific action ('detect the technology stack'), resource ('project'), and scope ('runtime, framework, database hints, and frontend info'). It explicitly distinguishes from sibling 'inspect_project' by noting it's 'faster and lighter', providing clear differentiation.

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

    Usage Guidelines5/5

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

    The description provides explicit guidance on when to use this tool versus alternatives: 'Faster and lighter than inspect_project' directly compares it to a sibling tool. This gives clear context for choosing between detection methods based on speed vs. thoroughness.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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