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daedalus

mcp-z3-prover

list_variables

Retrieve a list of all variables that have been created in the current session. Useful for tracking defined variables before adding constraints.

Instructions

List all created variables.

Returns: A dictionary containing a list of all variable references.

Example: >>> create_int_var("x") 'int:x' >>> create_bool_var("flag") 'bool:flag' >>> list_variables() {'variables': ['int:x', 'bool:flag']}

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?

No annotations are provided, so the description carries full burden. It clearly states the return format and includes an example, indicating this is a read-only query with no side effects.

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 extremely concise, with two sentences and an example. It front-loads the core purpose immediately.

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 the tool has no parameters, an output schema exists (per context), and the description fully explains the return structure with an example, it is completely adequate for an agent to invoke correctly.

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

Parameters5/5

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

The tool has zero parameters, and the description correctly mentions none. The example confirms no input is required. Schema coverage is 100%, so no additional information is needed.

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 'List all created variables' with a specific verb and resource, distinguishing it from sibling tools like create_int_var and solve. The example reinforces the exact functionality.

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 implicitly tells when to use (to retrieve all variable references) but does not explicitly exclude scenarios or mention alternatives. Given sibling tools are entirely different operations, 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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