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yorifuji

MCP iOS Simulator Screenshot

by yorifuji

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is singular and clearly defined, making it impossible for an agent to misselect between non-existent alternatives.

    Naming Consistency5/5

    A single tool inherently has perfect naming consistency, as there are no other tools to compare against. The tool name 'get_screenshot' follows a clear verb_noun pattern, which would be consistent if more tools existed.

    Tool Count2/5

    A single tool is too few for most practical server purposes, as it severely limits functionality and flexibility. While the server's name suggests a focused domain (iOS Simulator screenshots), one tool feels thin and incomplete for even basic operations like listing simulators or managing screenshots.

    Completeness2/5

    The tool surface is severely incomplete for the implied domain of iOS Simulator interactions. It only provides screenshot capture, with obvious gaps such as listing available simulators, starting/stopping simulators, or managing screenshot files, which are essential for a coherent workflow.

  • Average 2.9/5 across 1 of 1 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

  • This repository is archived. Archived repositories automatically receive an F maintenance tier.

  • 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 full burden for behavioral disclosure. 'Capture a screenshot' implies a read operation, but it doesn't specify whether this requires specific simulator states, permissions, or has side effects. The description lacks information about error conditions, what happens if no device is booted, or the format/location of output beyond what's in parameter descriptions.

    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 states the core purpose without unnecessary words. It's appropriately sized for a straightforward tool and gets directly to the point. Every word earns its place in conveying the essential function.

    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?

    For a tool with no annotations and no output schema, the description is insufficiently complete. While the purpose is clear, it lacks important behavioral context about how the tool operates, what it returns, error handling, and dependencies. The description doesn't compensate for the absence of structured metadata that would help an agent understand the tool's behavior and constraints.

    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?

    With 100% schema description coverage, all parameters are well-documented in the schema itself. The description adds no additional parameter information beyond what's already in the schema descriptions. This meets the baseline expectation when schema coverage is complete, but doesn't provide extra semantic context.

    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 ('Capture') and target resource ('screenshot from iOS Simulator'), making the purpose immediately understandable. It lacks sibling differentiation, but since there are no sibling tools, this doesn't reduce clarity. The description is specific enough to distinguish this from other potential screenshot tools.

    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, prerequisites, or context. It simply states what the tool does without indicating appropriate scenarios or limitations. While there are no sibling tools to differentiate from, the description offers no usage context whatsoever.

    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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