statefarm_bundle_recommendations

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

There are no annotations, so the description must carry the behavioral disclosure. It does convey that the tool 'analyzes' and 'suggests' rather than executes a purchase or quote, which is useful read-only context. However, it does not explicitly state that no policy is created, that recommendations are non-binding estimates, or whether any external system is affected.

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?

Two concise sentences with no filler. The first sentence front-loads the core action, and the second explains the analysis approach. Every phrase contributes useful meaning, and there is no redundant restatement of the schema.

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 tool's moderate complexity, the detailed schema, and the absence of an output schema, the description provides a solid overview of what the tool does and roughly what it returns (bundle suggestions with savings potential). It could be slightly more complete by stating the output format or emphasizing that only zip_code is required, but the schema compensates for those gaps.

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 parameters are already well documented. The description does not add much beyond mentioning the policy types involved in bundling, which maps to current_policies. Since the schema carries the full semantic load, the baseline score of 3 is appropriate.

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 states a specific action ('Get personalized insurance bundle recommendations') and a clear resource scope: analyzing current coverage and suggesting bundle savings across auto, home, life, and renters. This clearly differentiates it from siblings like statefarm_get_quote or statefarm_policy_details, which are about quotes or policy lookup rather than bundle recommendations.

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 gives clear context for when the tool is appropriate: when a customer wants to save money by bundling multiple insurance lines. It does not explicitly name alternatives or exclusions, but the purpose is distinct enough that an agent can infer when to prefer this over the quote or policy tools.

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