UX Laws MCP

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

No annotations are provided, so the description carries full burden. It mentions the tool analyzes based on 'working memory' law but doesn't disclose behavioral traits like what the analysis outputs (e.g., recommendations, scores, errors), whether it's read-only or mutative, performance characteristics, or error handling. The description adds minimal context beyond the basic purpose, leaving significant gaps for a tool with no annotation coverage.

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 moderately concise but includes unnecessary elements: it starts with an emoji and a Spanish translation ('La Memoria de Trabajo') that doesn't add value for tool selection. The core purpose is stated in the second sentence, but the first sentence is redundant fluff. It could be more front-loaded and streamlined without losing 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 complexity (cognitive analysis tool with 4 parameters), no annotations, and no output schema, the description is incomplete. It lacks details on what the analysis produces, how results are formatted, error conditions, or practical usage examples. For a tool that likely returns structured insights, the description should do more to compensate for the missing structured data, especially with no output schema provided.

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 thoroughly with descriptions and an enum for 'platform'. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain parameter interactions or provide examples). Baseline 3 is appropriate when the schema does the heavy lifting, though the description could have enhanced understanding of how parameters relate to the analysis.

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 para CUALQUIER PLATAFORMA' (Analyzes code or UI components according to this law for ANY PLATFORM). It specifies the action (analyze), target (code/UI components), and scope (working memory law, all platforms). However, it doesn't explicitly differentiate from sibling tools like analyze_millers_law or analyze_cognitive_load, which likely analyze different cognitive 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 implies usage context by stating it analyzes 'código o componentes UI' (code or UI components) for 'CUALQUIER PLATAFORMA' (ANY PLATFORM), which suggests when this tool is appropriate. However, it doesn't provide explicit guidance on when to use this versus alternatives like analyze_cognitive_load (which might be more general) or ux_full_audit (which might be broader). The platform list in the schema helps but isn't part of the description itself.

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