analyze_chunking

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions analyzing code/UI components but doesn't describe what the tool actually does: Does it return recommendations? Identify chunking violations? Score chunking quality? Provide before/after examples? The description is too abstract to guide an agent on what behavior to expect from invoking this tool.

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 relatively concise but poorly structured. It starts with a definition of chunking rather than stating the tool's purpose upfront. The second sentence is more useful but still vague. While not verbose, the structure doesn't effectively communicate the tool's function to an AI agent needing to select it.

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 tool with 4 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what analysis means in practice, what format results come in, what chunking law entails for UI/code analysis, or how this differs from other UX analysis tools. The agent would struggle to understand what invoking this tool actually accomplishes.

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. The description doesn't add any meaningful parameter semantics beyond what's in the schema - it mentions platforms but the schema's platform enum is more detailed. The description doesn't explain relationships between parameters or provide usage examples.

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 starts with a general definition of chunking ("Fragmentación") rather than stating what the tool does. It then says "Analiza código o componentes UI según esta ley" which is somewhat vague - it doesn't specify what kind of analysis it performs or what outputs it produces. The description doesn't clearly distinguish this from sibling tools like analyze_fitts_law or analyze_hicks_law which presumably analyze UI according to different laws.

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 mentions it works for "CUALQUIER PLATAFORMA" and lists many platforms, but provides no guidance on when to use this specific tool versus other analysis tools in the sibling list. There's no mention of what types of problems chunking analysis addresses, what questions it answers, or when it would be more appropriate than other UX analysis tools available.

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