Send a prompt to Amazon Q CLI to get AI assistance for chat, command translation, and status checks. Tailor responses with optional agent or model profiles.
Execute Amazon Q CLI with a prompt to get AI assistance
| Name | Required | Description | Default |
|---|---|---|---|
| agent | No | Agent/context profile to use (optional) | |
| model | No | Model to use (optional) | |
| prompt | Yes | The question or prompt to send to Amazon Q |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden for behavioral disclosure. It only mentions executing a CLI command to get AI assistance, without stating whether the operation is read-only, has side effects, requires authentication, or how long it may take.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one tight sentence with no filler, and it leads with the action and resource before the purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple prompt-passing tool, the description covers the basic purpose. However, with no output schema and sibling tools that could overlap, it omits any note about the response format, environment requirements, or when this tool is the right choice.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the schema already describes all three parameters (agent, model, prompt). The description adds no extra parameter semantics, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Execute') and resource ('Amazon Q CLI') and the purpose ('get AI assistance'). However, it does not differentiate from siblings like q_status or take_q, which could also involve running Q commands, so it loses the top point.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use ask_q instead of q_status, take_q, q_translate, or fetch_chunk. The description gives a general action but no context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.