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Praket7

agent-interop-runtime

by Praket7

set_model

Switch an existing thread to a different model when supported by the agent. Manages coordinated sessions across coding agents while keeping provider isolation.

Instructions

Set the model for an existing thread when supported.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes
threadIdYes
harnessIdNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.18

TDQS

C2.6/5.0
Behavior2/5

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

The annotations already indicate this is a mutating operation (readOnlyHint=false) but not destructive (destructiveHint=false), and the description adds little beyond that. It does mention 'existing thread' and 'when supported,' but it does not disclose what happens to the thread's conversation, whether the change persists, or whether unsupported models cause errors. No contradiction with annotations exists, but the behavioral context is thin.

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 is a single, direct sentence with no filler or redundant information. It front-loads the core action and resource. It is concise, though the vague 'when supported' could be replaced with more concrete conditions without hurting readability.

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

Completeness2/5

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

For a tool with three parameters and no output schema, the description is too thin to fully support correct invocation. It does not explain how to identify a supported thread, what model naming convention to use, or what harnessId means, and it offers no guidance relative to sibling tools. The flat schema and simple operation lower the bar, but 'when supported' still leaves critical context missing.

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

Parameters1/5

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

Schema description coverage is 0%, and none of the three parameters (threadId, model, harnessId) are described in the schema. The description only mentions 'model' and 'existing thread' generically, giving no semantics for valid model values, the role of threadId, or the optional harnessId. With zero schema coverage, the description needed to compensate and does not.

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 uses a specific verb ('Set') and a clear resource ('the model for an existing thread'), so an agent can understand the core action. It does not explicitly differentiate from siblings, but none of the siblings perform the same model-setting operation, so the ambiguity is mild. The phrase 'when supported' introduces some uncertainty but does not obscure the main purpose.

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

Usage Guidelines2/5

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

The description gives only a vague condition ('when supported') and no concrete guidance about when to call this tool versus alternatives, what makes a thread 'support' model changes, or what prerequisites must hold. It also does not explain when this tool should not be used or how it relates to siblings like list_models or send_message. This leaves usage decisions largely to inference.

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