ask_model

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 adds useful context about facilitator-style orchestration and user intervention between rounds, but does not disclose return format, rate limits, or required permissions. It is minimally adequate but could say more about what happens after the call.

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 two sentences, front-loaded with the core action ('Ask a single model a question') followed by a concise usage scenario. Every word earns its place, with no fluff or repetition.

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 relatively simple tool with no output schema and 100% schema parameter coverage, the description sufficiently captures the purpose and use case. It could have mentioned the return value or a note about session persistence, but this is not critical given the schema clarity.

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%, so the baseline is 3. The description does not add any additional parameter semantics beyond the schema, but the schema already documents model, prompt, context, and session_id clearly. No compensation needed.

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 clearly specifies 'Ask a single model a question' with a specific verb and resource, distinguishing it from sibling tools like ask_models (plural) and discussion-based tools (council_discuss, roundtable_discuss, debate_discuss). The scope is unambiguous.

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?

The description provides clear context: 'Use this for interactive, facilitator-style discussions where Claude Code orchestrates the conversation and the user can intervene between rounds.' It does not explicitly state when not to use it or name alternatives, but the context implies a single-model interactive use case.

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