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Glama

ask_model

Get a second opinion from a different model on designs, approaches, or tricky snippets via a one-shot prompt, returning the raw response without file access or actions.

Instructions

Get a second opinion from a different model — on a design, an approach, or a tricky snippet — or ask one when the user requests it. Sends a one-shot prompt over a direct API call and returns the raw response. The model has no file access and cannot take actions; for anything touching files use delegate. Don't use it for syntax or API details you already know: a cheap model is usually less reliable than you on those. Omit model to use the configured default.

Input Schema

NameRequiredDescriptionDefault
modelNoprovider/model or ollama:<name>, e.g. deepseek/deepseek-v4-flash, ollama:llama3. Omit to use the configured default; don't pick a premium tier
promptYesThe full question. The model has seen none of this conversation, so include the code and context it needs
systemNoOptional system prompt, e.g. a role or an answer format

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.4

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the burden and discloses key constraints: it is a one-shot direct API call, returns a raw response, the model has no file access and cannot take actions. It also warns that a cheap model may be less reliable than the agent itself. It does not cover cost, rate limits, timeout, or error behavior, which keeps it from a 5.

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 a compact paragraph with no wasted sentences. It front-loads the purpose, then adds behavioral constraints, exclusions, and the default-model note in a logical order.

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 simple three-parameter tool, no annotations, and no output schema, the description covers what the tool does, what it returns (raw response), and its key limitations. It is nearly complete, though it does not address failure modes or cost/timeout behavior.

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 description coverage is 100%, so the schema already documents all three parameters including the model format and default behavior. The description restates the default-model behavior but adds no meaningful parameter semantics beyond what the schema provides; 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: it gets a second opinion from a different model via a one-shot prompt. It explicitly contrasts itself with the sibling `delegate` for file-touching tasks, so an agent can distinguish them without opening either schema.

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

Usage Guidelines5/5

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

Gives clear when-to-use conditions (second opinion on design/approach/snippet, or when the user requests it) and explicit when-not-to-use guidance (don't ask for syntax/API details you already know). It names the alternative tool (`delegate`) for file-related work and explains how to use the default model.

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