analyze_selective_attention

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 states the tool 'analiza' (analyzes), which suggests a read-only operation, but doesn't clarify whether this is purely analytical or if it might modify anything. It doesn't mention authentication requirements, rate limits, output format, or what kind of analysis results to expect. The description provides only basic functional context without behavioral details.

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 reasonably concise with two sentences, but has some structural issues. The first sentence is a definition of selective attention rather than a direct tool description. The second sentence contains the actual tool description but includes an overly broad platform claim ('CUALQUIER PLATAFORMA') followed by a list that doesn't match the enum values exactly. The emoji adds visual noise without semantic value.

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?

For a 4-parameter analytical tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the analysis produces, what format results come in, or what constitutes a successful analysis. Given the complexity of analyzing code/UI against psychological principles across multiple platforms, the description should provide more context about the analytical methodology and expected outputs.

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 all parameters are documented in the schema. The description adds minimal value beyond the schema - it mentions analyzing 'código o componentes UI' (code or UI components) which aligns with the 'code' and 'component_description' parameters, and mentions 'CUALQUIER PLATAFORMA' which relates to the 'platform' parameter. However, it doesn't provide additional semantic context about how parameters interact or what constitutes good input.

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 (selective attention law). However, it doesn't explicitly differentiate from sibling tools like 'analyze_cognitive_load' or 'analyze_working_memory' which also analyze UI/code against psychological principles.

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 some usage context by stating it works for 'CUALQUIER PLATAFORMA' (any platform) and listing examples, which implies when this tool is applicable. However, it doesn't explicitly state when to use this specific law versus alternatives like 'analyze_fitts_law' or 'analyze_hicks_law', nor does it provide exclusion criteria or prerequisites for use.

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