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

Annotations already cover the safety profile (readOnly, non-destructive, closed-world), yet the description still adds real behavioral context: the revenue estimate vs. preliminary-range fallback for un-researched stores, an explicit error on unknown domains, and credit consumption. It stops short of describing result ordering or what an empty result set looks like.

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?

Three compact sentences, front-loaded with the matching definition, then usage, then failure/credit conditions. No filler and nothing repeated from 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?

No output schema exists, and the description covers the match criteria, the unknown-domain failure, and the credit cost, which is most of what an agent needs. It leaves the return shape (list of store records, presumably) implicit, which is a minor gap for a read-only lookup tool.

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 coverage is 100%, so 'domain' and 'limit' (default 10, max 15 on Free, hard cap 50) are fully documented in the schema already. The description adds the semantic of what counts as 'similar' for the matching revenue figure, but nothing about the domain normalization or limit behavior, so the baseline 3 is right.

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?

States a specific verb+resource ('Find Shopify stores similar to a given store') and immediately defines the matching rule: same category plus a 0.5x-2x annual-revenue window. That specificity separates it from get_store (single lookup) and search_stores (keyword search) without needing to open either schema.

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?

'Useful for competitive sets and lookalikes' gives a use context, and 'Uses search credits like search_stores' hints at a cost relationship with a sibling. However, it never states when to prefer this over search_stores, nor any exclusion such as what happens for a domain that is known but has no close matches.

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