analyze_fitts_law

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description explains what the tool does (analysis based on Fitts's Law) but lacks details on behavioral traits such as what the analysis outputs (e.g., metrics, recommendations), whether it's read-only or has side effects, performance characteristics, or error handling. It mentions platform versatility but doesn't clarify operational limits.

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 appropriately sized and front-loaded, starting with the law's definition and then stating the tool's function. It uses two sentences efficiently, with no redundant information, though the emoji and law name repetition are minor stylistic elements that don't detract significantly from clarity.

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 complexity of a UI analysis tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., analysis results, scores, suggestions), how to interpret outputs, or any limitations (e.g., supported code formats beyond listed platforms). For a tool with 4 parameters and analytical purpose, more contextual detail is needed.

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%, with clear descriptions for all four parameters (code, component_description, platform, context). The description adds minimal value beyond the schema, as it doesn't provide additional syntax, format details, or usage examples for the parameters. The baseline score of 3 is appropriate since the schema does the heavy lifting.

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 tool's purpose: 'Analiza código o componentes UI según esta ley' (analyzes code or UI components according to this law). It specifies the resource (code/UI components) and the analytical framework (Fitts's Law), though it doesn't explicitly distinguish it from sibling tools like analyze_hicks_law or analyze_jakobs_law beyond mentioning the specific law name.

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 implied usage context by stating it analyzes 'CUALQUIER PLATAFORMA' (any platform) and listing examples like Web, iOS, Android, etc. However, it doesn't explicitly state when to use this tool versus alternatives (e.g., other analysis tools in the sibling list) or mention any prerequisites or exclusions for its use.

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