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debabhinav1-hub

Test Generator MCP Server

by debabhinav1-hub
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Python

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have completely distinct purposes: one exports generated test scenarios to a file, while the other parses documents to extract text. There is no overlap in functionality or ambiguity between them.

    Naming Consistency4/5

    Both tools follow a verb_noun pattern (export_scenarios, parse_document), which is consistent. However, with only two tools, it's a small sample, but there are no deviations in naming style.

    Tool Count2/5

    With only two tools, the server feels thin for a 'Test Generator' purpose. It lacks core test generation functionality, such as creating or managing test cases, making the scope incomplete and the count too low.

    Completeness1/5

    The server is severely incomplete for test generation. It only includes export and parsing tools, missing essential operations like generating tests, editing scenarios, or running tests, which are critical for the domain.

  • Average 3/5 across 2 of 2 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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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 provided, the description carries full burden for behavioral disclosure. It mentions saving to a JSON file and storing in memory, but fails to clarify critical aspects: whether this is a write operation (implied by 'Save'), if it overwrites existing files, what 'in memory' means practically (e.g., persistence, access), or any permissions/rate limits. The description adds minimal context beyond the basic action.

    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 with zero waste—it directly states the tool's action, output format, and storage. Every word earns its place, and it's appropriately front-loaded with the core purpose.

    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 tool has an output schema (which should document return values), the description's job is reduced. However, with no annotations, 2 parameters (one required), and nested objects in the input, the description is incomplete: it lacks behavioral details (e.g., mutation effects, error handling) and parameter guidance. It's minimally adequate but has clear gaps for a tool that performs data export.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters2/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0%, so the description must compensate for undocumented parameters. It implies 'scenarios' as input but doesn't explain its structure or content requirements. It mentions 'JSON file' but doesn't link to the 'file_name' parameter or detail naming conventions. The description adds some meaning (e.g., scenarios are saved as JSON) but insufficiently clarifies the two parameters' roles and expectations.

    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 ('Save') and resource ('generated test scenarios'), specifying the output format ('JSON file') and storage location ('in memory'). It distinguishes from the sibling tool 'parse_document' by focusing on export rather than parsing. However, it doesn't explicitly differentiate scope or limitations beyond the basic operation.

    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. The description lacks context about prerequisites (e.g., scenarios must be generated first), exclusions, or comparisons to other tools. It implies usage for saving scenarios but offers no further direction.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • 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 states the tool reads files and returns plain text, but lacks details on error handling (e.g., invalid file paths, unsupported formats), performance (e.g., file size limits, processing time), or side effects (e.g., whether the file is modified). For a tool with no annotations, this is a significant gap in transparency.

    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: 'Read a PDF or DOCX and return plain text.' It is front-loaded with the core action and outcome, with zero wasted words. Every part of the sentence contributes essential information, making it highly concise and well-structured.

    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 tool's moderate complexity (reading documents) and the presence of an output schema (which likely describes the plain text return), the description is minimally adequate. It covers the basic purpose and input type but lacks details on usage context, behavioral traits, and parameter specifics. With no annotations and incomplete parameter guidance, it meets the baseline but has clear gaps.

    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 1 parameter with 0% description coverage, so the schema provides no semantic details. The description implies the parameter is a file path for PDF or DOCX files, adding some context beyond the schema's bare 'File Path' title. However, it doesn't specify format requirements (e.g., absolute vs. relative paths, supported extensions), so it partially compensates but not fully.

    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: 'Read a PDF or DOCX and return plain text.' It specifies the verb ('Read'), resource ('PDF or DOCX'), and outcome ('return plain text'), making the function unambiguous. However, it doesn't explicitly differentiate from the sibling tool 'export_scenarios', which might be a related but distinct operation, so it doesn't reach the highest score.

    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 doesn't mention the sibling tool 'export_scenarios' or any other potential tools for document processing, nor does it specify prerequisites like file accessibility or supported formats beyond PDF/DOCX. This leaves the agent without context for tool selection.

    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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