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

Goes well beyond the annotations: it explains the find-or-create semantics keyed on custom_id, that a genuinely new customer consumes a seat against the license's customer limit, and that the call returns customer_id and access_token. This is exactly the operational context annotations cannot 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-loaded with the core action, then idempotency, then the optionality caveat. Slightly long with four short paragraphs, but each carries distinct, non-redundant 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 one-parameter mutation whose return values are covered by the output schema, this description supplies idempotency, quota/seat implications, and the scope caveat. Nothing material is missing.

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, but the description adds meaning by tying custom_id to the find-or-create behavior ('an existing custom_id returns the existing customer rather than failing'), which is more than the schema's own description offers.

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: 'Create Mubert credentials for one of your product's users.' It clearly distinguishes the tool from siblings like generate_track and list_customers by naming the artifact produced (customer credentials).

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 a clear when-to-use rationale (each customer gets its own quota slice and live stream, so multi-user products should not share one) and an explicit when-not ('You do not need this to generate music through this server'). It does not name specific sibling alternatives, but the guidance is concrete.

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