Server Quality Checklist

Tool Scores

• imageA
  4.1/5.0
  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 key behaviors: window shadows/frames are excluded, output can be via file path or Base64 data, AI analysis occurs when a question is provided using auto-selected providers, and temporary files are deleted after analysis. The only minor gap is lack of explicit mention about permissions needed for screen capture or potential rate limits.

  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 appropriately sized and front-loaded with the core purpose. It efficiently covers capture targets, output formats, and analysis capability in a few sentences. The version information at the end ('PeepIt MCP 1.0.0-beta.1...') could be considered extraneous but doesn't significantly detract from the overall conciseness.

  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?

  For a 5-parameter tool with no annotations and no output schema, the description provides substantial context about behavior, use cases, and parameter interactions. It covers the dual functionality (capture + optional analysis) well. The main gap is the lack of information about return values or response structure, which would be important since there's no output schema. However, the description compensates well for the missing annotations.

  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 already documents all 5 parameters thoroughly. The description mentions some parameters (app_target, format, question) but doesn't add significant semantic value beyond what's in the schema. It provides context about how parameters interact (e.g., path behavior with format='data'), but the schema already covers most of this. Baseline 3 is appropriate when schema does the heavy lifting.

  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: 'Captures macOS screen content and optionally analyzes it.' It specifies the verb ('captures'), resource ('macOS screen content'), and optional analysis capability. It distinguishes from sibling tools 'analyze' and 'list' by focusing on capture functionality with optional analysis, rather than pure analysis or listing operations.

  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 about when to use this tool: for screen capture with optional AI analysis. It mentions specific use cases like targeting entire screens, app windows, or all windows of an app. However, it doesn't explicitly state when NOT to use this tool or when to prefer sibling tools like 'analyze' (which might be for analyzing existing images rather than capturing new ones).

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

• analyzeA
  4.3/5.0
  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: the tool analyzes local image files, supports both image understanding and OCR capabilities, allows flexible AI configuration, and provides examples of how it responds. It mentions server configuration dependencies but doesn't cover error handling, rate limits, or authentication requirements.

  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 clear sections: purpose statement, usage context, capabilities list, and example. While comprehensive, it could be slightly more concise - the capabilities section repeats information from the purpose statement, and the example is detailed but necessary. Most sentences earn their place by adding value.

  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?

  For a tool with 3 parameters, no annotations, and no output schema, the description provides substantial context about what the tool does and how to use it. It covers purpose, usage guidelines, capabilities, and provides a concrete example. The main gap is the lack of information about return values or error conditions, which would be helpful given the absence of an output schema.

  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 already fully documents all three parameters. The description adds minimal additional parameter semantics beyond what's in the schema - it mentions the types of questions that can be asked and provides an example, but doesn't add significant meaning beyond the comprehensive schema descriptions.

  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: analyzing pre-existing image files using AI models. It specifies the exact action ('analyzes'), resource ('image file from local filesystem'), and scope ('using configured AI model'). It distinguishes from sibling tools 'image' and 'list' by focusing on analysis rather than image manipulation or listing operations.

  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: 'when an image already exists (e.g., previously captured, downloaded, or generated) and you need to understand its content, extract text, or answer specific questions about it.' It also distinguishes capabilities (image understanding, OCR) and provides clear examples of appropriate use cases, making it easy to determine when this tool is the right choice.

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

• listA
  4.3/5.0
  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 well by describing capabilities, details available for windows (IDs, bounds, off-screen status), and server information. However, it doesn't mention performance characteristics, rate limits, or potential side effects of listing operations. The description is informative but could be more comprehensive about behavioral constraints.

  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 clear sections (Capabilities, Use Cases) and uses bullet points effectively. However, it includes version information ('PeepIt MCP 1.0.0-beta.1 using openai/gpt-4o, ollama/llava:latest') that doesn't add value for tool selection. The core content is front-loaded and efficient, but could be slightly more concise by removing the version details.

  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?

  For a tool with 3 parameters, 100% schema coverage, and no output schema, the description provides good contextual completeness. It explains what the tool does, when to use it, and provides concrete examples. However, without an output schema, the description could better explain what information is returned for each item_type, particularly for server_status which is mentioned but not detailed in the examples.

  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 already documents all parameters thoroughly. The description adds some context about fuzzy matching for app names and provides concrete examples of parameter usage, but doesn't add significant semantic meaning beyond what's already in the schema descriptions. The baseline of 3 is appropriate given the comprehensive schema 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 tool's purpose as 'Lists various system items on macOS, providing situational awareness' and specifies three distinct capabilities: listing running applications, application windows, and server status. It distinguishes itself from sibling tools 'analyze' and 'image' by focusing on listing rather than analysis or image capture.

  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 usage guidelines through 'Use Cases' section with concrete examples showing when to use each item_type. It distinguishes between different scenarios: checking if an app is running, finding specific windows for capture, and getting server status. The examples clearly demonstrate appropriate parameter configurations for each use case.

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