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ask_model

Send a prompt to a selected AI model and receive its response. Use this to directly query any configured provider by model alias.

Instructions

Send a prompt to a single configured model and return its response. Use this for a direct query to a specific provider/model.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
model_aliasYesModel alias from models.yaml (e.g. 'gpt', 'claude', 'gemini')
promptYesThe prompt / question to send.
system_promptNoOptional system prompt.
temperatureNoSampling temperature (0–2). Default 0.7.
max_tokensNoMax tokens in the response. Default 2048.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations provided, so description carries full burden. Describes the basic operation but omits potential side effects, error handling, or rate limits. For a straightforward query tool, this is minimally adequate.

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?

Two concise sentences with no wasted words. First sentence defines function, second adds usage guidance.

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 5 well-documented parameters and presence of an output schema, the description provides sufficient context for a simple tool. Does not explain return format, but output schema covers that.

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% with detailed parameter descriptions. The description adds no additional meaning beyond the schema, meeting the baseline for high coverage.

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?

The description clearly states the verb 'send a prompt' and the resource 'single configured model', and explicitly distinguishes from multi-model siblings like ask_many.

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 advises 'use this for a direct query to a specific provider/model', implying when to use it. Though it does not list alternatives explicitly, the context from sibling names provides differentiation.

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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