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nexus_switch_model

Switch the active AI provider and model to change the backend for all subsequent AI requests.

Instructions

Switch the active AI provider and model. After switching, all subsequent nexus_ask calls will use the new provider/model.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYesModel ID to use with this provider
providerYesProvider ID. Available: openai, gemini, anthropic, mistral, cohere, groq, together, perplexity, deepseek, xai, huggingface, openrouter, nvidia, fireworks, cerebras, sambanova, deepinfra, ai21, abacus, copilot, opencode-zen, custom, ollama, lmstudio, llamacpp, localai, vllm

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It usefully reveals that the switch is stateful and affects subsequent nexus_ask calls. However, it does not mention whether the change affects other tools, whether it persists across sessions, requires authentication, or returns any confirmation, leaving some behavioral ambiguity.

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 two short sentences with no filler. The core action is front-loaded, and the persistent effect is stated immediately after, making it easy for an agent to parse quickly.

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?

For a simple two-parameter tool, the description captures the essential context: what the switch does and what the consequence is for future calls. It does not explain failure modes, return values, or interaction with sibling tools, but these are less critical given the schema already documents the available providers.

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%, so both provider and model are already documented. The description adds no additional parameter meaning beyond what the schema provides, which matches the baseline for full schema coverage.

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 primary action—switching the active AI provider and model—and names the affected resource ('active AI provider and model'). It also adds a scoping detail by linking the switch to subsequent nexus_ask calls. However, it does not explicitly distinguish itself from sibling tools like nexus_configure, which might also manage provider/model settings.

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

Usage Guidelines3/5

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

The description implies when to use the tool: when you need subsequent nexus_ask calls to use a different provider/model. It does not explicitly state alternatives or when not to use it, nor does it mention related tools like nexus_list_models or nexus_reauth that may be relevant before switching.

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