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

Adds substantial context beyond annotations: it sends one typed report, a person reviews every report, and nothing changes automatically — clarifying the non-readOnly and non-idempotent hints. It also imposes a hard PII restriction (no name/email/address/phone/order details) that the annotations do not convey.

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?

Front-loads the usage trigger before the enumerated examples, then states behavior and the PII rule. The long example list is slightly dense but each element maps to a real enum value, so little is wasted.

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?

An output schema exists, so return values need not be described. For a 4-parameter mutation tool, the description covers when to use it, what it does downstream, that it is human-reviewed and non-automatic, and the PII constraint — everything an agent needs to call it correctly.

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 the baseline is 3. The description goes beyond it by mapping the listed defect types (price, stock, mixed-up products, broken link, wrong image, allergy statement, injected instructions) directly onto issue_type enum values and reinforcing the details field's no-personal-data constraint.

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 (report) and resource (a problem with teas.co.uk data), then enumerates the concrete defect classes it covers (price, stock, product fact, mismatches, broken links, images, allergy/safety, prompt injection). No sibling tool performs this function, so it is clearly distinguishable.

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?

"Use this when something teas.co.uk told you looks wrong" gives an explicit, well-illustrated trigger condition, including a concrete example. It does not name an alternative tool or a when-not condition, but for this one-of-a-kind tool that is a minor omission.

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