z3_check

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

With no annotations provided, the description carries the full burden. It clearly states the possible results (sat/unsat/unknown) and mentions that a model is included. This gives an accurate expectation of the tool's behavior, though it does not elaborate on potential errors or limitations.

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 followed by an example, which is concise and front-loaded. Every part adds value: the purpose is stated, the input is specified, and the example demonstrates usage. No unnecessary 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?

The tool is simple with one parameter and has an output schema, so the description need not cover return values. The provided example and result clarification sufficiently complete the picture, and the purpose is unambiguous within the context of sibling tools.

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?

Since the schema has 0% description coverage for the smt2 parameter, the description compensates with a concrete example, illustrating the expected string format. It clarifies that the input is an SMT-LIB2 formula, though the example includes multiple commands, which could be ambiguous.

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 identifies the tool's function: checking an SMT-LIB2 formula with Z3 and returning sat/unsat/unknown plus a model. The example and specification effectively distinguish it from sibling tools like solve_linear or solve_expression, which handle other kinds of formulas.

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 by specifying SMT-LIB2 input, which implicitly guides the agent to use this tool when the task involves SMT-LIB2 formulas. However, it does not explicitly mention when not to use it or name alternatives, so it stops short of a 5.

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