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

Adds real context beyond the annotations: the report becomes a support conversation answered by support, the identity/e-mail and company/ids attached, the 5-per-24h quota, the required auth session type, and the instruction to confirm wording with the user first. Annotations already flag non-idempotent/destructive/open-world, so the description earns credit for the auth, quota and side-effect detail rather than restating safety hints.

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 body contains two near-verbatim paragraphs saying the same thing (opens a support conversation, from the user's e-mail, with company and ids, support answers there, 5/day cap). Roughly half the text is redundant restatement, which dilutes a description that is otherwise front-loaded.

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 explained. The description covers side effects, auth requirements, quota, and user-confirmation duty for a mutation tool; only the conversation_id continuation behavior is left entirely to the schema.

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 all four parameters (including the detailed conversation_id protocol and the description content) are already documented in the schema. The description only loosely gestures at 'the interview or result ids given' and never mentions conversation_id, so it adds little beyond what the schema provides. Baseline 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?

States a specific verb and resource: 'Report a technical problem to JobMojito support', and clarifies the mechanism (opens a support conversation from the user's e-mail). It implicitly separates itself from submit_feature_request via the technical-problem framing, but never names that sibling explicitly, so differentiation relies on inference.

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?

Gives concrete preconditions: 'Confirm the wording with the user first', a rate limit ('at most 5 a day'), and the required token/role ('merchant, merchant owner or admin'). It does not say when to prefer this over submit_feature_request, which is the closest alternative in the sibling list.

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