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myuon

Refactor MCP

by myuon
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TypeScript
Hybrid

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: code_refactor modifies code by replacing patterns, while code_search only finds patterns and returns locations. There is no overlap in functionality, making it impossible to confuse them.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern with 'code_' as a prefix and descriptive suffixes ('refactor' and 'search'). The naming is uniform and predictable throughout the set.

    Tool Count2/5

    With only 2 tools, the server feels thin for a 'Refactor MCP' domain. While the tools cover basic search and replace operations, typical refactoring workflows might require more operations like rename, extract method, or analyze dependencies, leaving the surface incomplete.

    Completeness2/5

    The toolset is severely incomplete for a refactoring domain. It lacks essential operations such as renaming identifiers, extracting functions or variables, analyzing code structure, or handling refactoring across multiple files. Agents will face dead ends when attempting complex refactoring tasks.

  • Average 3.1/5 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

  • 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 provided, the description carries the full burden of behavioral disclosure. It mentions 'refactor code' which implies mutation/write operations, but doesn't specify whether this modifies files in-place, creates backups, requires confirmation, or has any safety mechanisms. It also doesn't describe error handling, performance implications, or what the tool returns. The description is too vague about the actual behavior beyond the basic operation.

    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 at just one sentence that directly states the core functionality. Every word earns its place: 'Refactor code' establishes the action, 'by replacing search pattern with replace pattern' explains the mechanism, and 'using regex' specifies the technology. There's no wasted verbiage or unnecessary elaboration.

    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 this is a mutation tool with 6 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what happens after refactoring (e.g., preview vs. apply, success/failure reporting), doesn't mention the optional parameters' purposes, and provides no safety warnings for a tool that modifies code. For a complex refactoring operation, more context is needed.

    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 all parameters are documented in the schema. The description adds minimal value beyond the schema by mentioning 'regex' and 'search pattern with replace pattern', which aligns with the schema's 'search_pattern' and 'replace_pattern' parameters. However, it doesn't explain the relationship between parameters or provide usage examples that would help understand how they work together.

    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 verb 'refactor' and the resource 'code', specifying it uses regex patterns for search and replace. It distinguishes from the sibling 'code_search' by indicating this is a modification operation rather than just searching. However, it doesn't specify what kind of refactoring (e.g., renaming, restructuring) or the scope beyond regex replacement.

    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 'code_search' tool, nor does it specify scenarios where regex-based refactoring is appropriate versus other refactoring methods. There's no information about prerequisites, limitations, or when not to use it.

    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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool searches and returns results, but lacks details on permissions, rate limits, error handling, or output format beyond file locations and line numbers, leaving gaps for a tool with 5 parameters.

    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 purpose and outcome without unnecessary words, 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 complexity (5 parameters, no annotations, no output schema), the description is minimal but covers the basic purpose. It lacks details on behavioral traits and output specifics, making it adequate but incomplete for full 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 all parameters. The description adds no additional meaning beyond what the schema provides, such as examples or usage tips for the parameters, meeting the baseline for high coverage.

    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 specific action ('Search for code patterns using regex') and the resource ('code'), with the outcome ('return file locations with line numbers'). It distinguishes from the sibling tool 'code_refactor' by focusing on search rather than modification.

    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 like 'code_refactor'. The description mentions the search functionality but does not specify scenarios, prerequisites, or exclusions for its use.

    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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