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SuperCrazyKaizen

macOS Automator MCP Server

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 completely distinct purposes with no overlap: execute_script runs automation scripts, while get_scripting_tips provides discovery and learning resources. An agent would never confuse these tools as one performs actions and the other provides information.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun naming pattern (execute_script, get_scripting_tips) with clear action-oriented verbs. The naming is perfectly consistent across the minimal tool set.

    Tool Count2/5

    With only 2 tools, this server feels severely underpowered for the ambitious scope of 'macOS automation.' While the tools are well-designed, a comprehensive automation server would typically need tools for managing workflows, monitoring automation status, or handling different automation technologies beyond just scripts.

    Completeness3/5

    The server covers the basic execute/discover workflow well, but lacks tools for managing automation workflows, scheduling tasks, or monitoring running automations. For a macOS automation server, there are notable gaps in lifecycle management and broader automation capabilities beyond script execution.

  • Average 4.6/5 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 is failing
  • 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

  • Behavior4/5

    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 does an excellent job describing execution characteristics: timeout behavior (default 60 seconds, 'Increase for potentially long-running operations'), output formatting options with detailed enum explanations, debugging features (include_executed_script_in_output, include_substitution_logs), and performance reporting (report_execution_time). The only gap is it doesn't mention security implications or permission requirements for executing scripts.

    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 perfectly structured and appropriately sized. It begins with a clear purpose statement, then organizes complex parameter information into logical sections with bold headers. Every sentence adds value: examples illustrate usage, notes explain defaults and recommendations, and technical details are presented clearly. Despite the complexity, there's no wasted text or redundancy.

    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 the high complexity (11 parameters, nested objects, no annotations, no output schema), the description is remarkably complete. It covers all parameters thoroughly, explains execution behavior, provides usage examples, and references the sibling tool. The only minor gap is the lack of information about return values or error handling since there's no output schema. For a tool with this level of complexity, it's nearly comprehensive.

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

    Parameters5/5

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

    With 0% schema description coverage for 11 parameters, the description must and does fully compensate. It provides comprehensive semantic explanations for all parameters organized into logical groups: Script Source (kb_script_id, script_content, script_path), Script Inputs (input_data, arguments), and Execution Options (language, timeout_seconds, output_format_mode, include_executed_script_in_output, include_substitution_logs, report_execution_time). Each parameter gets clear usage guidance, examples, and relationships between parameters.

    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: 'Automate macOS tasks using AppleScript or JXA (JavaScript for Automation) to control applications like Terminal, Chrome, Safari, Finder, etc.' It specifies the verb ('automate'), resource ('macOS tasks'), technology ('AppleScript or JXA'), and target applications. This distinguishes it from the sibling tool 'get_scripting_tips' which is for finding script IDs rather than execution.

    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 context for when to use different script sources: 'kb_script_id' is 'Preferred' for pre-defined scripts, 'script_content' is 'Good for simple or dynamic scripts', and 'script_path' is for scripts from server paths. It references the sibling tool 'get_scripting_tips' to find IDs. However, it doesn't explicitly state when NOT to use this tool or what alternatives might exist beyond the sibling.

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

  • Behavior4/5

    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 effectively describes key behaviors: it's a read-only discovery tool (implied by 'discover' and 'knowledge base'), outputs results in Markdown format, and mentions database refresh functionality. However, it lacks details on rate limits, error handling, or authentication needs, which are minor gaps.

    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 well-structured with sections like 'Primary Use Cases & Parameters' and 'Best Practices,' making it easy to scan. However, it is lengthy (over 300 words), which may be excessive for a tool description. Some details could be condensed without losing clarity, though all content is relevant and front-loaded with key purpose.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the complexity (5 parameters, 0% schema coverage, no output schema, no annotations), the description is highly complete. It covers purpose, usage, parameters, outputs (Markdown format), and integration with sibling tools. No significant gaps remain for an agent to understand and invoke the tool correctly in context.

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

    Parameters5/5

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

    The schema description coverage is 0%, so the description must fully compensate. It does so comprehensively: each of the 5 parameters is explained with clear semantics, including functionality, examples (e.g., for 'search_term'), and interactions (e.g., 'limit' applies to 'search_term' or 'category' but not 'list_categories'). This adds significant value beyond the bare schema.

    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: to 'discover how to automate any app on your Mac' using a 'knowledge base of AppleScript/JXA tips and runnable scripts.' It specifies the verb 'discover' and resource 'tips and scripts,' distinguishing it from the sibling tool 'execute_script' which is for execution rather than discovery. This is specific and avoids tautology.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides explicit guidance on when to use this tool: it states it 'should be the FIRST CHOICE when aiming to automate macOS tasks... before attempting to write scripts from scratch.' It also mentions alternatives, advising to 'use its ID with `execute_script` tool for precise execution' after discovery. This includes clear when-to-use and when-not-to-use scenarios.

    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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  • Evaluate tool definition quality.

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