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get dedicated endpoint

get_dedicated_endpoint
Read-onlyIdempotent

Fetch a dedicated endpoint's live status, frozen hourly price, unbilled accrued cost, and routing key to poll a deployment until running or check spend.

Instructions

Returns one dedicated endpoint's current view (live status, frozen hourly price, unbilled accrued cost, routing key) — use it to poll a deploy until RUNNING or to check spend. GET /v1/dedicated/{id} (API-key scope: read). Returns: A single endpoint object, snake_case: { id, name, description, model_name, flavor_name, gpu_type, gpu_count, region, min_replicas, max_replicas, status, enabled, hourly_rate_usd, pending_cost_usd, routing_key, base_url, last_metered_at, created_at }. Notes: Scope via requiredScopeFor is 'read'; the local dedicated apiKeyActor does not enforce scopes. Implemented by listing the workspace's endpoints (live-reconciled) and picking the id, so it costs a full list call. 404 'Endpoint not found'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesDedicated endpoint id (must belong to the key's workspace; deleted endpoints 404).
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TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnly, idempotent, and non-destructive; the description adds meaningful behavior beyond that: the exact GET route, API-key scope, note that the local apiKeyActor does not enforce scopes, the fact that it is implemented via a full live-reconciled list call, and the 404 behavior. This is rich, non-obvious operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose and use cases, then provides the route, return shape, and critical caveats. Every sentence carries useful information, and despite its length, no part is redundant or wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Even without an output schema, the description enumerates the full snake_case object shape, explains auth scope behavior, ownership requirements, implementation cost, and error semantics. For a one-parameter read tool, this is complete enough for an agent to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the single parameter's description already covers the workspace ownership constraint and deleted-endpoint 404 behavior. The description repeats the 404 and scoping context but adds little beyond the schema for the parameter itself, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: 'Returns one dedicated endpoint's current view' with concrete fields (live status, frozen hourly price, unbilled accrued cost, routing key). It clearly distinguishes itself from list_dedicated_endpoints by returning a single object, and even names its use cases, so an agent can tell it apart from siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says when to call it: 'use it to poll a deploy until RUNNING or to check spend.' This gives clear context and intent. It does not explicitly name alternatives or when-not-to-use it, but the primary use cases are well conveyed.

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

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