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daedalus

mcp-z3-prover

reset_solver

Clear all variables, constraints, and model data from the solver to start a new problem fresh.

Instructions

Reset the solver state.

Clears all variables, constants, constraints, and model data. Useful when starting a new problem.

Returns: A dictionary with status and a success message.

Example: >>> create_int_var("x") 'int:x' >>> add_constraint("int:x > 5") {'status': 'success', 'constraint': 'int:x > 5'} >>> reset_solver() {'status': 'success', 'message': 'Solver reset successfully'} >>> list_variables() {'variables': []}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations, the description fully discloses the tool's effects: clearing all solver state. It also shows the return value via an example, providing full transparency.

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

Conciseness5/5

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

The description is concise, front-loaded with a summary, uses bullet points for clarity, and includes a relevant example. Every sentence adds value.

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

Completeness5/5

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

Given no parameters and no annotations, the description covers purpose, usage, return value, and provides an example. It is complete for this simple tool.

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

Parameters4/5

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

The tool has zero parameters, so the baseline score is 4. The description correctly does not attempt to explain parameters.

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 the tool resets the solver state, listing exactly what is cleared (variables, constants, constraints, model data). This distinguishes it from sibling tools that add or query state.

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

Usage Guidelines4/5

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

The description explicitly says 'Useful when starting a new problem,' indicating when to use it. It does not mention when not to use it or alternatives, but the context is clear enough.

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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