bulk_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 batching support (up to 20 queries), which is useful context. However, it lacks critical details: it doesn't specify rate limits, authentication needs, error handling, or what the response looks like (no output schema). For a search tool with no 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 and front-loaded: two sentences with zero waste. The first sentence states the core purpose, and the second adds crucial behavioral context (batching). Every sentence earns its place by providing distinct, valuable information.

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 1 parameter with full schema coverage and no output schema, the description is moderately complete. It covers the tool's purpose and batching behavior but lacks details on response format, error conditions, or performance constraints. For a search tool with batching, more context on output structure or limitations would improve completeness.

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 the single parameter 'X-User-Agent' with its type and default. The description doesn't add any parameter-specific information beyond what's in the schema. Baseline 3 is appropriate when the schema does the heavy lifting, though the description could have explained parameter relevance to batching.

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: 'Search local businesses on Google Maps' specifies the action (search) and resource (local businesses on Google Maps). It distinguishes from siblings like 'search' (generic) and 'search_in_area' (geographically constrained) by emphasizing bulk/batching capability. However, it doesn't explicitly contrast with all siblings like 'business_details' or 'reverse_geocoding'.

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 clear context for when to use this tool: 'Batching of up to 20 queries is supported in a single request' implies it's optimal for multiple searches at once. It doesn't explicitly state when NOT to use it or name alternatives (e.g., use 'search' for single queries), but the batching context strongly guides usage decisions.

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