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 the core behavior (comparing layouts and returning differences) and the purpose (finding responsive design issues), but lacks details on potential side effects, performance characteristics, error handling, or authentication needs. For a tool with no annotations, this is adequate but leaves gaps in behavioral understanding.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is perfectly concise and front-loaded, consisting of two sentences that efficiently convey the tool's purpose, output, and usage. Every sentence earns its place: the first explains what the tool does and returns, while the second provides the usage context. There is zero waste or redundancy.

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

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

Given the tool's moderate complexity (comparing layouts across viewports) and the absence of both annotations and an output schema, the description is minimally complete. It covers the core functionality and use case but lacks details on output format, error conditions, or limitations. Without structured fields to rely on, the description should ideally provide more context, but it meets basic adequacy.

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

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

The input schema has 100% description coverage, providing clear documentation for all parameters (url, viewport_a, viewport_b, selector). The description adds minimal value beyond the schema, only implicitly reinforcing the purpose of viewport comparison. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't significantly enhance parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Compare the layout of a URL at two different viewport widths'), identifies the resource (URL layout), and distinguishes from siblings by focusing on responsive design comparison rather than layout mapping or screenshot capture. It explicitly mentions the outcome ('Returns a list of elements whose size or CSS styles differ') and use case ('find responsive design issues').

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

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 this tool ('Use this to find responsive design issues'), which implicitly differentiates it from siblings like viewpo_get_layout_map (likely for mapping layouts) and viewpo_screenshot (for capturing visuals). However, it does not explicitly state when NOT to use it or name specific alternatives, keeping it at a 4 rather than a 5.

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

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 the output ('Returns element hierarchy with tags, classes, bounding rects, and computed CSS styles') and purpose, but lacks details on performance, error handling, or authentication needs, which are relevant for a tool that likely involves network requests.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose in the first sentence, followed by a concise usage guideline. Every sentence earns its place by adding value, with no redundant or verbose language, making it highly efficient.

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

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

Given the tool's moderate complexity (3 parameters, no output schema, no annotations), the description is mostly complete. It explains what the tool does and its output format, but could benefit from mentioning potential limitations (e.g., timeouts, JavaScript-rendered content) to fully guide an agent.

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

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

The schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional parameter semantics beyond what the schema provides, such as examples or edge cases, resulting in a baseline score of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Extract the DOM layout tree'), target resource ('of a URL'), and scope ('at a given viewport width'), distinguishing it from sibling tools like viewpo_compare_viewports and viewpo_screenshot by focusing on structural analysis rather than comparison or visual capture.

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

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 this tool ('to understand page structure and find layout issues'), but does not explicitly mention when not to use it or name alternatives among the sibling tools, such as using viewpo_screenshot for visual issues instead.

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

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 the core behavior (capturing screenshots and returning base64 JPEGs) but lacks details about potential side effects (e.g., network requests, rate limits, authentication needs, or error handling). The description doesn't contradict annotations, but it's incomplete for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise and front-loaded, with two sentences that efficiently convey the tool's purpose and usage. Every word earns its place, and there's no redundant or verbose language, making it easy to parse quickly.

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

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

Given the tool's moderate complexity (capturing screenshots with configurable viewports), no annotations, and no output schema, the description is somewhat incomplete. It covers the basic purpose and output format but lacks details on behavioral aspects like error cases, performance implications, or how the output is structured. This is adequate but leaves clear gaps for an agent to fully understand the tool's behavior.

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

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

The schema description coverage is 100%, so the schema already fully documents the parameters (url and viewports). The description adds minimal value beyond the schema by implying the tool's purpose relates to viewport widths, but it doesn't provide additional semantic context or usage examples for the parameters. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Capture screenshots'), the resource ('a URL at one or more viewport widths'), and the output format ('base64 JPEG images'). It distinguishes from siblings by focusing on visual capture rather than comparison or layout analysis, making the purpose immediately understandable and distinct.

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

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 this tool ('to SEE what a webpage looks like at different screen sizes'), which implicitly suggests it's for visual inspection. However, it doesn't explicitly state when NOT to use it or name alternatives like the sibling tools, leaving some guidance gaps.

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