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realmindsai

Configurable Command MCP Server

by realmindsai
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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 between tools. The tool's purpose is clearly defined as reading multiple document types using pandoc, making it distinct by default.

    Naming Consistency5/5

    Since there is only one tool, naming consistency is inherently perfect. The tool name 'read_docs_by_list' follows a clear verb_noun pattern, and there are no other tools to compare it against for inconsistency.

    Tool Count2/5

    A single tool is too few for a server named 'Configurable Command MCP Server', which suggests a broader scope of configurable commands. This minimal toolset feels thin and underdeveloped for the implied purpose, indicating a significant mismatch.

    Completeness1/5

    The server's name implies configurability and command execution, but the single tool only covers document reading. There are obvious gaps, such as lacking tools for configuration management, command execution, or other document operations, making the surface severely incomplete for the stated purpose.

  • Average 3.4/5 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

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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

  • Behavior3/5

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

    No annotations provided, so description carries full burden. Adds value by disclosing the underlying engine ('using pandoc') and supported formats. However, lacks critical behavioral details: safety properties (destructive vs read-only), return value format, error handling for unsupported files, and performance characteristics (large file handling).

    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?

    Single sentence of 9 words. Front-loaded with verb. Every word earns its place: identifies operation, scope, supported formats, and implementation mechanism. No redundancy or extraneous text.

    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 low complexity (single array parameter) and 100% schema coverage with pattern validation, the description adequately covers the tool's purpose and supported formats. No output schema exists; description would benefit from indicating return format, but this is not critical given the tool's narrow scope.

    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 clear descriptions of the 'files' array and supported extensions. Description reinforces the file types mentioned in the schema pattern but adds no additional semantic detail about path requirements, array size limits, or how the files are processed beyond 'using pandoc'. Baseline 3 appropriate for high schema coverage.

    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?

    States specific verb ('Read'), resource ('documents'), and supported formats ('PDF, Word, HTML'). Tool name confirms scope ('by_list'). Mentions implementation ('using pandoc') which adds specificity. Deducting 1 point because it doesn't clarify what 'read' means in terms of output (extracted text, raw bytes, etc.).

    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 provided on when to use this tool versus alternatives, prerequisites (e.g., file accessibility), or when-not-to-use. While there are no siblings, the description fails to indicate appropriate contexts (e.g., 'use this to extract text content from documents').

    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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