devtools_computed_css

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

The description is consistent with the readOnlyHint annotation. It explains that the tool returns a dict of property-value pairs and implies no side effects. This added context beyond the annotation is sufficient for safe invocation.

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 concise and well-structured: a summary sentence, a bullet list of example use cases, and the return format. Every sentence provides useful information with no 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 simplicity (2 parameters, no enums, output schema present), the description covers all necessary context: purpose, parameters, return type, and typical use cases. It is complete for an AI agent to use correctly.

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 has 100% coverage, and the description adds value by explaining that the 'properties' parameter expects comma-separated names and that empty defaults to a useful set. This helps the agent understand parameter semantics beyond the schema.

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 it returns computed CSS properties. It includes specific use cases like checking display:none, color, font, CSS variable resolution, and grid/flex dimensions, which distinguishes it from sibling tools like devtools_css_variables and devtools_element_info.

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 guidance on when to use the tool ('to understand why an element looks wrong') with concrete examples. It does not explicitly mention when not to use it or compare to alternatives, but the context is sufficiently clear for an AI agent to decide.

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