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MushroomFleet

UNO-MCP

by MushroomFleet
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TypeScript

Server Quality Checklist

50%
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  • Latest release: v1.0.0

  • Disambiguation2/5

    The tools 'custom_enhance_text' and 'enhance_text' have overlapping purposes, both focused on enhancing story pages, with only a vague distinction based on technique selection versus using all techniques. This creates ambiguity where an agent might struggle to choose between them for a given enhancement task. The 'analyze_text' tool is more distinct but the enhancement tools lack clear boundaries.

    Naming Consistency4/5

    All tools follow a consistent snake_case naming pattern with a verb_noun structure (e.g., analyze_text, enhance_text). The naming is predictable and readable, with only minor deviation in 'custom_enhance_text' where the adjective 'custom' adds some variation but maintains the overall convention.

    Tool Count3/5

    With only 3 tools, the server feels thin for a domain like story analysis and enhancement, potentially lacking coverage for broader operations. While it covers basic analyze and enhance functions, the low count may limit agent capabilities in handling more complex workflows or additional CRUD-like actions.

    Completeness2/5

    The tool set is severely incomplete for a story analysis and enhancement domain, as it only includes analysis and enhancement without any CRUD operations (e.g., create, update, delete story pages) or lifecycle management. This creates significant gaps that will likely cause agent failures when trying to perform full workflows beyond simple text processing.

  • Average 2.7/5 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 ISC License.

  • This repository includes a README.md file.

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

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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 states the tool 'enhances' text, implying a transformation, but doesn't describe the nature of the enhancement, potential side effects, rate limits, or output format. This is a significant gap for a tool with multiple parameters and no output schema.

    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, efficient sentence that front-loads the core action ('enhances a story page'). It avoids unnecessary words, but could be more informative given the tool's complexity, making it slightly under-specified rather than perfectly concise.

    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 tool's complexity (7 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'enhance' entails, how techniques interact, or what the output looks like, leaving critical gaps for an agent to understand and use the tool effectively.

    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 7 parameters. The description mentions 'selected techniques' but doesn't add meaning beyond the schema, which already details each enhancement technique and parameter. The baseline score of 3 reflects adequate coverage by the schema alone.

    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 states the tool 'enhances a story page using selected techniques,' which provides a general purpose but lacks specificity. It mentions the resource ('story page') and verb ('enhances'), but doesn't clarify what 'enhance' means or how it differs from sibling tools like 'enhance_text' and 'analyze_text', leaving the purpose somewhat vague.

    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 offers no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'enhance_text' or 'analyze_text', nor does it specify prerequisites, contexts, or exclusions for usage, leaving the agent without clear direction on tool selection.

    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 mentions 'using all techniques' but doesn't explain what these techniques are, whether the enhancement is reversible, what permissions or rate limits apply, or what the output looks like. For a tool with no annotations and an implied mutation ('enhances'), this leaves critical behavioral traits undisclosed.

    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, efficient sentence that front-loads the core action. It avoids unnecessary words and gets straight to the point. However, it could be slightly more structured by explicitly separating purpose from constraints, but overall it's appropriately concise for the tool's complexity.

    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 tool's implied complexity (enhancing text with multiple techniques) and lack of annotations and output schema, the description is incomplete. It doesn't explain what 'enhance' entails, what techniques are used, or what the result looks like. For a tool that likely modifies content, more context is needed to guide the agent effectively.

    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 schema description coverage is 100%, with clear descriptions for both parameters ('text' and 'expansionTarget'). The description adds no additional meaning beyond what the schema provides, such as examples or contextual usage. However, since the schema adequately documents the parameters, a baseline score of 3 is appropriate as the description doesn't detract from the schema's clarity.

    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 states the tool 'enhances a story page using all techniques to meet expansion target', which provides a vague purpose. It specifies the resource ('story page') and goal ('meet expansion target'), but the verb 'enhances' is generic and doesn't clearly differentiate from sibling tools like 'analyze_text' or 'custom_enhance_text'. The description lacks specificity about what 'enhance' means operationally.

    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 sibling tools like 'analyze_text' or 'custom_enhance_text', nor does it specify contexts, prerequisites, or exclusions for usage. The agent must infer usage based on the tool name alone, which is insufficient for informed selection.

    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 mentions analysis and report generation but lacks details on what 'insights' entail, whether the operation is read-only or has side effects, performance characteristics, or error handling. This is a significant gap for a tool with no annotation coverage.

    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 core functionality ('Analyzes a story page') and adds the outcome ('generates a report with insights') without any wasted words. It is appropriately sized for the tool's apparent complexity.

    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 doesn't explain what the 'report' or 'insights' look like, potential limitations, or how it differs from sibling tools. For a tool with no structured behavioral or output information, more context is needed to guide effective 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?

    The schema description coverage is 100%, with the single parameter 'text' documented as 'The story page text to analyze or enhance'. The description adds no additional parameter semantics beyond what the schema provides, so the baseline score of 3 is appropriate as the schema handles the documentation adequately.

    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 with a specific verb ('analyzes') and resource ('a story page'), and specifies the output ('generates a report with insights'). However, it doesn't explicitly differentiate from sibling tools like 'custom_enhance_text' or 'enhance_text', which appear to have related but potentially different functions.

    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 its siblings ('custom_enhance_text' and 'enhance_text'), nor does it mention any prerequisites, alternatives, or exclusions. It only states what the tool does without contextual usage information.

    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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