assign_carrier_subscriber_plan

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

With no annotations, the description carries the full burden of disclosing behavioral traits, and it does so extensively. It reveals that this is a 'Guarded write' with a sequence of safety behaviors: read-before, no-op when already on the plan, confirm=true requirement, write kill-switch, and read-after. It also discloses testability limitations and the upstream rejection of archived or unknown plans. This far exceeds typical descriptions and gives the agent a clear mental model of side effects and backend expectations.

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 dense but every sentence earns its place. The opening sentence gives the purpose immediately, followed by needed caveats (testability, rejection, guarded behavior) and then parameter explanations. There is no fluff or repetition; even the testability warning is operationally relevant because it sets expectations for how the tool is validated. The structure front-loads the essential information.

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?

For a mutating operation with a guard flag and upstream validation, the description covers all invocation-critical aspects: purpose, prerequisites (source tools for IDs), required confirm flag, optional key_label routing, success no-op condition, failure modes (archived/unknown plan), and backend safety checks. An output schema exists and is noted in context, so the absence of return-value documentation is acceptable. This is a complete picture for an agent to call the tool 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 description coverage is 0%, so the description must compensate, and it fully does. Each parameter is given an explicit semantic: subscriber_id is 'the subscriber UUID from list_carrier_subscribers', plan_id is 'the service-plan UUID to assign (from list_carrier_service_plans)', confirm 'must be true to apply the change', and key_label is 'optional configured API-key label'. This is exactly the kind of grounding the schema lacks, providing provenance and constraints that the bare property names do not convey.

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 opens with a direct, specific statement: 'Assign a service plan to a subscriber (PUT .../subscribers/{id}/plan).' The verb, resource, and HTTP endpoint are explicit, making the tool's purpose unmistakable and clearly distinct from sibling carrier tools like suspend/resume/create/update. The inclusion of the endpoint syntax further concretizes the operation.

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 strong usage context by specifying that subscriber_id comes from list_carrier_subscribers and plan_id from list_carrier_service_plans, implicitly instructing the agent to gather IDs from those tools first. It also states the confirm parameter must be true to apply the change, clarifying a critical precondition. However, it does not explicitly name alternative tools or state when not to use this one, so it stops short of full usage exclusion guidance.

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