UX Laws MCP

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

No annotations are provided, so the description carries the full burden. It mentions analyzing according to the Doherty Threshold law and the 400 ms threshold, but doesn't disclose key behavioral traits: what the analysis outputs (e.g., a report, score, or recommendations), whether it's a read-only or mutation operation, any performance implications, or error handling. The description is vague about the actual behavior beyond the high-level concept.

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: it starts with the law definition and immediately states the tool's function. The second sentence adds platform scope efficiently. There's minimal waste, though the emoji and law explanation could be seen as slightly extraneous but not excessive.

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 output schema, and no annotations), the description is incomplete. It lacks details on what the analysis entails, the output format, any limitations, or how results should be interpreted. Without annotations or output schema, the description should do more to explain the tool's behavior and results, but it remains high-level and conceptual.

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 4 parameters with descriptions. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain how parameters interact or provide usage examples). With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't detract either.

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: analyzing code or UI components according to the Doherty Threshold law for any platform. 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 the specific law name, which is implied but not stated as a distinguishing factor.

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 implies usage context by stating it analyzes 'CUALQUIER PLATAFORMA' (ANY PLATFORM) and listing examples like Web, iOS, Android, etc. However, it doesn't provide explicit guidance on when to use this tool versus alternatives (e.g., other analysis tools in the sibling list) or any exclusions. The platform scope is broad but not framed as comparative advice.

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