MCP Server Box

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 AI usage and optional agent selection, but lacks details on behavioral traits such as rate limits, authentication needs, response format, or error handling. The description is minimal and does not compensate for the absence of 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 and front-loaded: the first sentence states the purpose clearly. The Args and Returns sections are structured but could be more concise. Overall, it avoids unnecessary verbosity, though some sentences (like the Args list) are functional rather than explanatory.

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 (AI interaction with files), lack of annotations, 0% schema coverage, and no output schema, the description is incomplete. It does not address key contextual aspects such as response structure, error cases, or integration with sibling AI tools, making it inadequate for informed tool selection.

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 0%, so the description must compensate. It lists parameters with brief explanations (e.g., 'The ID of the file to ask about'), but does not add meaningful semantics beyond what the schema titles imply. For example, it does not explain file ID format constraints or prompt best practices, leaving gaps in understanding.

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: 'Ask a question about a file using AI.' It specifies the verb ('ask'), resource ('file'), and method ('using AI'), which is specific and actionable. However, it does not explicitly distinguish it from sibling tools like 'box_ai_ask_file_multi_tool' or 'box_ai_ask_hub_tool', which limits differentiation.

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 no guidance on when to use this tool versus alternatives. It does not mention sibling tools like 'box_ai_ask_file_multi_tool' (for multiple files) or 'box_ai_ask_hub_tool' (for hubs), nor does it specify prerequisites or exclusions. Usage is implied by the tool name but not explicitly stated.

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