get_ordering_guidance

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

No annotations are provided, so the description carries full burden. It mentions analysis and suggestions but doesn't disclose behavioral traits such as whether this is a read-only operation, if it requires authentication, rate limits, or what the output format looks like (e.g., structured advice vs. text). For a tool with no annotations, this leaves significant gaps in understanding how it behaves.

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 concise and front-loaded, with the core purpose stated first. Both sentences earn their place by elaborating on analysis and strategy. However, it could be slightly more structured by explicitly separating purpose from details.

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. It doesn't explain what the tool returns (e.g., guidance format, error handling), and with 2 parameters, it lacks details on behavioral aspects like side effects or dependencies. For a tool that provides AI guidance, more context on output and usage 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 ('store_id' and 'user_request') with descriptions. The description adds marginal value by implying parameters are used for analysis and suggestions (e.g., 'store_id' for deals, 'user_request' for preferences), but doesn't provide additional syntax or format details beyond what the schema provides.

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: 'Get AI guidance on how to build the best order based on user preferences.' It specifies the verb ('Get AI guidance') and resource ('order'), and mentions analysis of deals, pizza counts, and ordering strategy. However, it doesn't explicitly differentiate from siblings like 'search_menu' or 'get_menu' which might also provide ordering information.

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 doesn't mention prerequisites, exclusions, or compare to siblings like 'search_menu' for menu items or 'get_coupons' for deals. The context is implied (building an order), but no explicit usage rules are given.

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