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ask_agent

Ask a question to the local AI agent to receive an answer, leveraging Ollama models with call tracing.

Instructions

Ask the Muse Glimmer AI agent a question.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavior. It states 'ask a question,' which implies a query or read operation, but it does not disclose any side effects, response format, permissions, or limitations. This is a significant gap for a tool with no annotation support.

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 single, short sentence with no wasted words. The verb is front-loaded and the resource is clear. It is appropriately concise for a simple tool, though this brevity comes at the cost of detail.

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?

The tool has an output schema (not shown), so return values may be covered, but the description lacks any context about the nature of questions, expected inputs, or edge cases. An agent has no information about what kinds of prompts are valid or what the response will look like, making it incomplete for a one-parameter tool with no annotations.

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

Parameters2/5

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

The schema has 0% description coverage, and the description does not mention the 'prompt' parameter at all. It adds no information about the expected format, content, or purpose of the prompt beyond what the parameter name itself implies. The description fails to compensate for the schema coverage gap.

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 action (ask) and the resource (Muse Glimmer AI agent). It is specific enough for a tool with no siblings, though it is generic and could be more detailed about the scope of questions. The verb+resource is clear and not tautological.

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?

No explicit guidance on when to use this tool versus alternatives, and there are no sibling tools. The description does not mention any prerequisites, context, or conditions for use, leaving the agent to infer that it should be used when a question needs answering.

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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