compare_products

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

No annotations are provided, so the description carries the transparency burden. It discloses important behaviors: case-insensitive matching, refusal on ambiguous names with candidates listed, document selection logic (general conditions over IPID, newest edition), and inclusion of superseded flags in the response. This is substantial, though it does not address potential side effects (e.g., read-only nature, error handling for no matches) that could be expected.

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 compact yet information-dense. Every sentence serves a purpose: first defines the main action, then details matching rules, next explains ambiguity handling, and finally document selection. No fluff or redundancy; ideal structure for AI consumption.

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?

With an output schema present, return values are already documented, so the description can focus on behavior. It covers key edge cases (ambiguous names, document selection) and usage constraints. However, it omits potential error scenarios or handling for mismatched array lengths, which could leave the agent uncertain in unusual cases. Still, for a tool of this complexity, it is largely complete.

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%, meaning the description must compensate. It does so excellently: explains product_names (case-insensitive matching), insurer_slugs (same length/order, pins names), and 'on' (dimension choices). Even country, while not explicit, is self-evident and not problematic. The description adds significant semantic meaning beyond the raw schema.

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 function: 'Compare 2+ products side by side on one dimension: coverages | exclusions | deductibles.' This is a specific verb+resource with explicit scope, distinguishing it from sibling tools like get_product (single product) and find_overlap (overlap analysis).

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 usage context: use this when comparing multiple products on a chosen dimension. It also gives practical guidance on passing insurer_slugs and handling ambiguous names. However, it does not explicitly contrast with alternatives or state when not to use the tool, so it falls short of a 5.

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