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 states the tool 'detects automatically' but doesn't disclose behavioral traits like accuracy, limitations, whether it's deterministic or probabilistic, what happens with ambiguous code, or if it requires internet access. For a detection tool with zero annotation coverage, this is a significant gap.

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 two sentences and an emoji. The first sentence clearly states the purpose, and the second adds context about the input. However, the emoji and formatting slightly reduce efficiency, and the second sentence could be more front-loaded.

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 no annotations and no output schema, the description is incomplete for a detection tool. It doesn't explain what the output looks like (e.g., platform name, confidence score), any error conditions, or limitations. For a tool that performs analysis based on code input, more contextual information 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?

Schema description coverage is 100%, so the schema already documents both parameters thoroughly. The description adds no additional meaning about parameters beyond what's in the schema (e.g., it doesn't explain how 'code' and 'file_extension' interact or provide examples). Baseline 3 is appropriate when 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 with a specific verb ('detecta') and resource ('plataforma'), and indicates it's based on provided code. It distinguishes itself from sibling tools that analyze UX principles rather than detect platforms. However, it doesn't specify what types of platforms it can detect (e.g., web frameworks, mobile platforms).

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?

No guidance is provided on when to use this tool versus alternatives. While sibling tools like 'ux_compare_platforms' and 'ux_list_platforms' exist, the description doesn't explain how this detection tool differs from them or when it's preferred. Usage context is implied but not explicit.

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