ask_all

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 the key trait of parallel execution, which goes beyond the name. However, it does not mention result format, failure handling, or the effect of the timeout parameter, leaving some behavioral aspects unspecified.

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, zero waste. The first sentence states the action, the second gives the usage context. Information is front-loaded and every word earns its place.

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?

The tool is simple with four parameters and no output schema. The description covers purpose and usage. However, it does not describe how results are returned (e.g., per-agent responses), which would be valuable given the lack of an output schema.

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?

The input schema provides complete descriptions for all parameters (100% coverage), so the baseline is 3. The description does not add any additional parameter-specific semantics beyond what the schema already provides.

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 states the tool's function: 'Ask multiple agents the same question in parallel.' This specifies a verb, resource, and core behavior, and distinguishes it from sibling tools like ask_agent (single agent) and collaborate (agents working together). The multi-agent comparison use case is explicit.

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 a clear use case: 'Use for explicit multi-agent comparison.' It gives clear context for when to use the tool, but does not explicitly name alternatives or state when not to use it, which would push it to a 5.

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