Server Quality Checklist

Tool Scores

• capture_windowA
  3.9/5.0
  Behavior3/5

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

  No annotations are provided, so the description must carry the full burden. It discloses that the tool captures a live, visible window and uses a local Ollama model, which implies real-state analysis and privacy considerations. However, it does not mention required permissions, whether it brings the window to front, or any side effects, leaving notable behavioral gaps.

  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 two efficient sentences with the core purpose front-loaded, followed by a single high-value comparison sentence. No wasted words.

  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?

  While the description covers purpose and differentiates from a sibling, the tool is complex (6 params, nested object, no output schema). It does not explain the return format (e.g., text from the vision model), prerequisites (e.g., screen recording permission), or the effect of crop/scale parameters. These gaps are significant for an agent unfamiliar with the tool.

  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?

  The input schema provides 100% coverage with detailed descriptions for all six parameters, including the nested crop object and model default. The tool description adds no extra parameter semantics, so a baseline of 3 is appropriate.

  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 action ('Capture a specific app window currently visible on screen and analyze it with a local Ollama vision model'), specifies the resource (specific app window), and differentiates from the sibling tool analyze_screenshot. The verb is specific and the scope is explicit.

  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 explicitly names an alternative (analyze_screenshot) and contrasts their behavior ('this sees your real browser with your logged-in session and live state'), providing a clear use case ('ideal for testing local apps'). It lacks an explicit 'when not to use' statement, but the contrast implies it.

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

• analyze_screenshotA
  4.3/5.0
  Behavior4/5

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

  With no annotations, the description carries the full burden of behavioral disclosure. It reveals that the tool runs a headless browser, uses a local Ollama vision model, and explains the slicing mechanism for full-page captures to preserve detail. This goes beyond the schema and provides meaningful insight into how the tool behaves, though it omits return format and potential side effects.

  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 two sentences, front-loaded with the primary purpose, followed by usage guidance and a key behavioral note. Every sentence earns its place with no redundancy or filler.

  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 covers the main use case, login-page alternative, and full-page behavior, but it does not explicitly specify what the tool returns (e.g., analysis text, screenshot, or both). Given the absence of an output schema, this is a notable gap for a tool with 8 parameters and a potentially complex response.

  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 baseline is 3. The description reinforces the full_page parameter's behavior ('sliced into segments and sent as multiple images') but does not materially add meaning beyond what the schema already documents for other 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 states a specific action ('Take a screenshot of a URL in a headless browser and analyze it with a local Ollama vision model') and distinguishes the tool from siblings by explicitly contrasting with capture_window for login pages. This makes the tool's purpose unambiguous and clearly differentiated.

  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 gives explicit usage context: 'Good for public pages' and directs users to 'use capture_window instead' for login-protected pages. It also advises on full_page usage for content below the fold, covering when to use this tool versus an alternative.

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

• locate_elementA
  4.4/5.0
  Behavior4/5

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

  Since annotations are absent, the description carries the behavioral disclosure burden. It reveals key behaviors: the use of a local Ollama vision model ('Claude never sees the image'), privacy preservation, and the coordinate system semantics for viewport_bounds. It does not describe failure handling, permissions, or output format, but the disclosed traits are meaningful and non-obvious.

  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 three sentences, each earning its place: core purpose, model/privacy, and coordinate behavior with a concrete example. The critical viewport_bounds guidance is front-loaded after the purpose, making the most actionable information easy to find. No filler words 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?

  Considering the tool's complexity (nested viewport_bounds object, 5 params, no output schema, no annotations), the description covers the essential missing context: coordinate semantics and the crucial Chrome-specific computation. It omits edge cases like element-not-found behavior or return error structure, but for a coordinate-returning tool, the provided detail is sufficient for effective use.

  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 already documents all 5 parameters with 100% coverage, so the baseline is 3. The description adds significant value by explaining exactly how to compute viewport_bounds for Chrome and why it changes the returned coordinates. This provides meaning beyond the schema's static field definitions.

  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 opens with an explicit, specific verb+resource statement: 'Find a UI element in an app window and return its click coordinates.' This clearly differentiates the tool from siblings like analyze_screenshot (which analyzes an image) and capture_window (which captures a window). The returned artifact (click coordinates) is unambiguous.

  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 concrete guidance for the Chrome-specific case, including a detailed formula for viewport_bounds and the consequence of omitting it (absolute vs. viewport-relative coordinates). It does not explicitly name alternative tools or state when not to use this tool, but it offers clear contextual usage instructions.

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