smart_search

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'intelligent searches' and 'natural language queries,' which imply some processing, but doesn't describe key behaviors: whether this is read-only or has side effects, how results are formatted, if there are rate limits, authentication needs, or error handling. For a search tool with zero annotation coverage, this leaves significant gaps.

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 a single, efficient sentence that front-loads the core purpose. There is no wasted text or redundancy, making it highly concise and well-structured for quick understanding.

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 (search tool with natural language processing), no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, how results are structured, or any behavioral traits like performance or limitations. For a tool that likely processes queries intelligently, more context is needed to guide effective use.

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 ('query' and 'limit') with examples and defaults. The description adds minimal value beyond the schema—it reiterates 'natural language queries' but doesn't provide additional syntax, constraints, or usage context. Baseline 3 is appropriate when the 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: 'Perform intelligent searches across your inventory with natural language queries that can include multiple criteria.' It specifies the verb ('perform searches'), resource ('inventory'), and method ('natural language queries'). However, it doesn't explicitly distinguish this from potential sibling search tools (none are listed among siblings, but the description doesn't address this).

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 mentions 'natural language queries' but doesn't specify scenarios where this is preferred over structured search tools or other inventory access methods. No exclusions, prerequisites, or comparison to sibling tools (like 'get_inventory_stats') are provided.

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