ask_group_model

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

Annotations supply only openWorldHint=true, so the description must carry the behavioral load, and it does add real context: local execution is private and free, while a remote group's model costs credits and is "read by that computer" (a meaningful data-exposure warning). It says nothing about latency, what waitMinutes governs, failure behavior, or what the response contains.

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?

Two sentences, front-loaded with the privacy/cost framing that determines tool selection, with no filler. The phrasing "Ask the model run by the person's own group of computers" is slightly tangled, but every clause carries information.

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 5-parameter generation tool with no output schema and thin annotations, the definition covers the privacy/cost tradeoff well but leaves the operational surface thin — timeout semantics, token limits, and return shape are all unaddressed. An agent could pick the tool correctly but would be guessing on how to configure the call.

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 only 20% (just `model`), so the description needs to compensate and largely does not. It reinforces the meaning of `model` (only for another group's model) but leaves `system`, `maxTokens`, `waitMinutes`, and even `prompt` unexplained beyond their names, including the unusual 120-minute maximum wait.

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 names a specific verb and resource ("Ask the model run by the person's own group of computers") and scopes it to the group's own hardware rather than the public cloud. It stops short of naming how it differs from sibling tools such as ask_ai_model or ask_open_model, so the agent must infer the distinction from the privacy/cost framing.

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?

It gives one concrete routing rule: pass `model` to use another group's offered model, and it points to list_group_models for discovery, noting that path costs credits. It offers no guidance on when to prefer this tool over ask_ai_model/ask_open_model, and nothing on when to include `system` or how to size `maxTokens`/`waitMinutes`.

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