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andredezzy

deep-directory-tree-mcp

by andredezzy
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Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap with other tools. The tool's purpose is clearly distinct by default.

    Naming Consistency5/5

    A single tool inherently follows a consistent naming pattern, as there are no other tools to compare against. The name 'get_deep_directory_tree' uses a clear verb_noun structure.

    Tool Count2/5

    One tool is too few for a server named 'deep-directory-tree-mcp', which suggests a scope that might include operations like listing, filtering, or modifying directory trees. A single get operation feels thin and incomplete for this domain.

    Completeness2/5

    The tool surface is severely incomplete for a directory tree domain. It only provides a get operation, with obvious gaps such as creating, updating, deleting, or searching directory trees, which are essential for basic CRUD coverage.

  • Average 2.7/5 across 1 of 1 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.

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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, the description carries the full burden of behavioral disclosure. It only states the action without detailing output format, performance implications, error handling, or system impacts. This is inadequate for a tool that likely returns structured data and may have depth/exclusion constraints.

    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 extremely concise with a single phrase, front-loaded and without unnecessary words. It efficiently conveys the core intent, though this brevity contributes to gaps in other dimensions.

    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 no annotations, no output schema, and a tool with behavioral complexity (e.g., tree generation with exclusions), the description is incomplete. It fails to explain return values, error cases, or practical use, leaving significant gaps for agent understanding.

    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 parameters like 'path' and 'options' with defaults. The description adds no parameter semantics beyond what the schema provides, meeting the baseline for high coverage but not enhancing understanding.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose3/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description 'Get deep directory tree' states the basic action (get) and resource (directory tree), but lacks specificity about what 'deep' means or how it differs from a shallow tree. Without sibling tools, differentiation isn't needed, but the purpose remains vague about the nature of the operation beyond the literal interpretation.

    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 on when to use this tool versus alternatives or any prerequisites. The description does not mention context like file system exploration or debugging scenarios, leaving the agent with no usage cues beyond the tool name.

    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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