list dedicated endpoints

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

Beyond the readOnly/idempotent annotations, the description discloses several non-obvious behaviors: the dedicated routes do not enforce key scopes, deleted endpoints are excluded, status is live-reconciled with DB fallback, catalog/provider failures return a 400, and billing accrues per GPU-hour. This is exactly the kind of behavioral context an agent needs.

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 long but dense and well-organized: the core purpose is front-loaded, followed by a structured field list and then essential caveats. Every sentence adds operational value, and there is no tautology or filler.

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?

With no output schema, the description fully compensates by covering return shape, field meanings, auth caveats, reconciliation behavior, deletion filtering, error cases, and the billing model. An agent has enough information to call the tool correctly and interpret its results.

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?

The tool has zero parameters and schema description coverage is 100%, so there is no parameter ambiguity to resolve. The description still adds meaning by explaining response-field semantics such as hourly_rate_usd being frozen at deploy and pending_cost_usd being unbilled accrued GPU-hours.

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 and resource: lists the workspace's dedicated (reserved-GPU) inference endpoints, with live-reconciled status, frozen hourly price, and unbilled cost. It clearly distinguishes this from the create/update/delete/get dedicated endpoint siblings and from list_dedicated_templates.

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 explicitly frames the use case: 'use it to monitor what is running and what it is costing,' and provides the HTTP method and read scope. It does not explicitly mention when to prefer get_dedicated_endpoint for a single endpoint, but the context is clear enough.

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