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

No annotations are provided, so the description carries the burden. It discloses the output format (P(yes) in [0,1]) and the binary nature of the question, which is useful. However, it does not disclose whether the tool is deterministic, whether it requires a specific state format, or any side effects (though likely none).

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 a single sentence that is front-loaded with the core purpose and includes the key output detail. Every word earns its place; no filler.

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 only two string parameters and an output schema, so the description is mostly adequate. However, with no annotations and no parameter semantics, an agent may not know how to construct a valid 'state' or 'question' string, or how the output schema maps to the probability. Slightly more context would be needed for full confidence.

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 0%, and the description does not explain what 'state' or 'question' mean beyond their names. The description adds the context that the question is yes/no and the output is a probability, but it does not clarify the expected format or semantics of the two parameters, leaving the agent to infer.

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 ('answer') and resource ('a yes/no question about a state'), and clarifies the output is P(yes) in [0,1]. It is clear about what the tool does, though it does not explicitly differentiate from siblings like decide or classify.

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 implies usage for yes/no questions about a state, but provides no explicit guidance on when to use this tool versus siblings (decide, classify, score). The context is clear enough for a simple binary question, but no exclusions or alternatives are mentioned.

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