Customer Lookup

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

With no annotations, the description must reveal behavioral traits. 'Look up' and 'returns' imply a read-only, non-mutating operation, and the mention of returned fields gives some transparency. However, it does not address what happens when no customer is found, how the tool behaves when multiple identifiers are provided, or whether any authorization is needed.

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 very concise: two sentences, a clear, simple lookup action, and a usage note. All sentences are used to fill a purpose-oriented or behavioral gap, with no fluff.

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 simple tool shape (had 3 params, no output schema), the description is a very complete level: names the keys, provides return values, and positions itself as the first step for a typical flow. You may still be missing the empty-result/one-of-three requirement, but that is an edge condition that is not normally needed to drive a first lookup.

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% and each field already has a clear description, so the baseline is appropriate. The text adds the concept of three comparable lookup keys, but it does not specify that at least one key is needed or what happens with conflicting/multiple inputs. The description adds meaningful context, but does not exceed the baseline.

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 verb ('look up'), a clear resource ('customer record'), and the exact lookup keys (customer ID, email, phone). It also previews the returned data (account status and tier), making the tool's purpose distinct from the sibling tools at a glance.

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?

It provides clear ordering guidance: 'Call this first in the context of nearly every flow,' which is an explicit usage directive. But it does not enumerate exclusions or explicitly reference an alternative tool, so the contrast with siblings (e.g., retrieve_status, update_crm_record) is left slightly to inference.

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