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nmelo

Prompt Refiner MCP Server

by nmelo

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    With only a single tool, there is no possibility of confusion between tools. The tool's purpose is clearly defined and distinct.

    Naming Consistency5/5

    The single tool name 'promptrefiner' is clear and descriptive. While it doesn't follow a verb_noun pattern, consistency is trivially maintained with only one tool.

    Tool Count3/5

    The server has exactly one tool, which feels thin. However, the tool's purpose is narrowly scoped (prompt refinement), and the single tool encapsulates a complete workflow, making the count borderline but not extreme.

    Completeness4/5

    The tool covers the full prompt refinement lifecycle: start, clarify, and export with multiple templates. It appears functionally complete for its domain, though additional utilities (e.g., listing previous refinements) could be imagined.

  • Average 4.2/5 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

  • Behavior4/5

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

    With no annotations, the description carries the full burden. It discloses that the tool 'tracks your refinement steps and formats the output' and places control of the process on the user. It doesn't mention side effects or persistence, but it clearly outlines the interaction model and templates. This goes beyond a tautological statement and provides meaningful behavioral context.

    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 longer than average, but it is well-structured with a workflow, key aspects, and template list. The main purpose is front-loaded, and each section earns its place. Some redundancy exists (e.g., aspect list repeated in workflow and key aspects), but it remains readable and informative rather than bloated.

    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?

    The description explains the modes and templates but is vague about the return value—what exactly the refined prompt looks like or how to interpret the output. Since there is no output schema, this is a gap. Additionally, the stateful nature of 'tracks your refinement steps' is implied but not explicitly described (e.g., how to chain multiple CLARIFY calls). Overall, it's useful but not fully complete for a tool with multiple modes and no output schema.

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

    Parameters4/5

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

    The schema covers 100% of parameters, but the description adds significant value by grouping parameters into modes (Mode 1, 2, 3), explaining the meaning of each aspect, and listing available export templates with descriptions. This contextual mapping helps an agent understand how to combine parameters correctly, which the bare schema does not convey.

    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 tool's purpose: 'systematically refining vague ideas into well-structured prompts.' It specifies the action (refining), the resource (ideas/prompts), and provides a structured workflow. Even without sibling tools, it defines its unique role.

    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 usage context through a step-by-step workflow (START, CLARIFY, EXPORT), details on which parameters to use for each mode, and guidance on when to ask questions. It doesn't explicitly mention exclusions or alternatives (no siblings exist), but the context is sufficient for an agent to decide when to invoke the tool.

    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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