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Z3 Check

z3_check
Read-onlyIdempotent

Check satisfiability of SMT-LIB2 logical scripts, returning sat/unsat/unknown plus a model. Solves inequalities, boolean combinations, and multi-variable constraints.

Instructions

Use z3_check, not symbolic(op="solve"), for satisfiability over inequalities, boolean combinations, or several variables at once: sat/ unsat/unknown plus a model. Example: '(declare-const x Int)(assert (> x 5))(check-sat)'.

unsat is graded solver_proven — see grade_basis for the engine version and timeout bound it was decided within. sat is graded ungraded: it's a real decided answer, just not a proof — reserving solver_proven for unsat means a counterexample can never wear a proof grade. unknown carries no proof either way and is also graded ungraded.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
smt2YesSMT-LIB2 script to check for satisfiability, e.g. '(declare-const x Int)(assert (> x 5))(check-sat)'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.12.0
    • addedInput schema / properties / smt2 / description
      Added value: +"SMT-LIB2 script to check for satisfiability, e.g. '(declare-const x Int)(assert (> x 5))(check-sat)'"
  2. Changed1 schema field changedv0.11.0
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "title": "z3_checkDictOutput",
+  "type": "object"
+}
  3. Changed4 schema fields changedv0.2.0
    • removedInput schema / additionalProperties
      Removed value: -false
    • addedInput schema / properties / smt2 / title
      Added value: +"Smt2"
    • addedInput schema / title
      Added value: +"z3_checkArguments"
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "type": "object"
-}New value: +null
  4. First observedv0.1.0

TDQS

A4.4/5.0
Behavior5/5

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

The description goes beyond the readOnly/idempotent annotations by explaining output semantics: sat/unsat/unknown plus a model, and the important grading distinction (unsat is a proof; sat and unknown are not). It also points to grade_basis for timeout/engine details.

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 slightly longer than strictly necessary but is front-loaded with the core purpose and example, then adds grading semantics. No wasted sentences.

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?

For a read-only, idempotent SMT check tool, the description fully covers when to use it, what it returns, how results are graded, and where to find engine details. An agent has enough context to invoke it correctly.

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% and the smt2 parameter is already described with an example. The description restates this example but adds no substantial parameter-level meaning beyond what the schema provides.

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 names a specific verb and resource ('z3_check'), a concrete task (satisfiability over SMT-LIB inequalities/boolean combinations), and explicitly contrasts itself with symbolic(op='solve'). An agent can immediately tell what this tool does and what it is not for.

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?

It says to use z3_check instead of symbolic(op='solve') for satisfiability checking and lists qualifying cases. It does not fully describe when symbolic should be used instead, but the key alternative and decision trigger are explicit.

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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