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solve

Execute Z3 Python code to solve SMT constraints and check satisfiability of logical formulas.

Instructions

Execute Z3 Python code to solve SMT constraints.

The code can use any Z3 Python API functions. Common imports (Solver, Int, Real, Bool, And, Or, Not, etc.) are pre-loaded.

Example:

x = Int('x')
y = Int('y')
solver = Solver()
solver.add(x + y == 10)
solver.add(x - y == 4)
if solver.check() == sat:
    print(solver.model())

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYesZ3 Python code to execute
timeout_msNoTimeout in milliseconds (default: 30000)
Behavior2/5

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

No annotations are provided, and the description fails to disclose key behaviors: return value (e.g., stdout), error handling, side effects (if any), or timeouts beyond the parameter. The example shows printing output, but the actual output format is unspecified.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two paragraphs and an example, which is helpful. However, the example adds length; it could be more front-loaded with essential information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Without an output schema, the description should explain the return value and side effects. It does not, leaving the agent uncertain about what the tool actually produces or modifies. Error behavior and state changes are also missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the description adds minimal value beyond what the schema already provides. It mentions pre-loaded imports and gives an example, but does not clarify the code format or constraints.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool executes Z3 Python code to solve SMT constraints, including an example. It distinguishes itself from siblings like check_sat and prove by being a general-purpose Z3 execution tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for arbitrary Z3 Python code but does not explicitly state when to use this tool versus alternatives like solve_logic_program or solve_smtlib.

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

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