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routing_policy_update

Directs you to update a deployment's request-routing policy in its source code and redeploy, because the policy cannot be changed through the API.

Instructions

[WRITE][risk=medium] Switch a deployment's request-routing policy.

NOTE: Ray Serve's request-routing policy is a code-level option on the @serve.deployment decorator, NOT a field settable over the Dashboard REST API — there is no REST endpoint for it. This tool therefore refuses with a teaching error rather than pretend; change the policy in the deployment's source and redeploy.

Args: application: Serve application name. deployment: Deployment name. policy: Desired routing policy (prefix_aware / round_robin / session_affinity). target: Inference target name from config; omit for the default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
policyYes
targetNo
deploymentYes
applicationYes
Behavior4/5

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

With no annotations provided, the description carries full burden, and it does well: it discloses the refusal behavior, explains the underlying limitation (no REST endpoint), and states that it will return a teaching error. It does not describe the exact error format or side effects, but since it is a refusal stub, that is less critical. The disclosure is honest and helps an agent avoid expecting a real update.

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

Conciseness4/5

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

The description begins with a useful [WRITE][risk=medium] tag and a one-line summary, followed by a necessary explanatory note and clear args section. It is a little longer than strictly needed, but every sentence contributes context, especially the note about the REST limitation. The structure is logical and easy to scan.

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

Completeness4/5

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

Given the tool's unusual nature (a stub that refuses), the description thoroughly explains why it exists and what will happen. It covers all parameters, states the limitation, and provides an alternative. It does not mention what the 'teaching error' message contains or whether any state changes occur, but for this kind of tool, that is acceptable. Overall it is complete enough for an agent to decide not to call it unless explicitly instructed to inform the user.

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

Parameters5/5

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

The input schema provides no descriptions (0% coverage), so the description fully compensates. It explains each of the four parameters: application (Serve application name), deployment (deployment name), policy (with a list of allowed values: prefix_aware / round_robin / session_affinity), and target (with instruction to omit for default). This adds meaningful guidance beyond the schema and is complete for all parameters.

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

Purpose4/5

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

The description clearly states the nominal purpose ('Switch a deployment's request-routing policy') and then immediately qualifies it by explaining this tool actually refuses with a teaching error because no REST endpoint exists. This distinguishes it from sibling deployment tools and makes its actual behavior explicit. The verb+resource is present, though the contrast between the nominal action and real behavior could be confusing, so not a perfect 5.

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?

The description explicitly says the policy is code-level and cannot be set over the Dashboard REST API, and it recommends changing the source and redeploying. This is a clear 'when not to use' directive and gives an alternative action. It does not explicitly say 'use this tool when you want to inform the user that this cannot be done via API,' but the implication is strong and adequate.

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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