analyze_teslers_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. It describes the analysis action but lacks details on what the tool returns (e.g., a report, score, or recommendations), any rate limits, error conditions, or performance characteristics. The description is functional but insufficient for a tool with no annotations.

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 with three sentences: an introduction to Tesler's Law, the core purpose, and platform scope. It's front-loaded with the law definition, but the purpose statement is clear. There's minimal waste, though the law explanation could be slightly trimmed for conciseness.

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 (analysis tool with 4 parameters), no annotations, and no output schema, the description is incomplete. It doesn't explain what the analysis outputs (e.g., a complexity score, recommendations, or a report), leaving the agent uncertain about the tool's result. For a tool with rich input schema but no output information, this is a significant gap.

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?

Schema description coverage is 100%, so the schema already documents all four parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain how 'code' and 'component_description' interact or provide examples). Baseline 3 is appropriate when 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 verb 'analiza' (analyzes) and the resource 'código o componentes UI' (code or UI components). However, it doesn't explicitly differentiate from sibling tools like 'analyze_fitts_law' or 'analyze_hicks_law' beyond mentioning Tesler's Law specifically.

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 implied usage context by stating it works for '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 any exclusions. The guidance is limited to platform compatibility.

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