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Each step in every SKILL.md now carries labeled Action, Expectation, and Result blocks so the agent can mechanically execute, verify, and branch at each stage. Format chosen after comparing three variants (indented blocks, inline keywords, tables) on a prove-validity simulation; indented blocks scored highest on routing completeness and checkability. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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| name | description |
|---|---|
| optimize | Solve constrained optimization problems using Z3. Supports minimization and maximization of objective functions over integer, real, and bitvector domains. |
Given a set of constraints and an objective function, find the optimal value. Z3 supports both hard constraints (must hold) and soft constraints (weighted preferences), as well as lexicographic multi-objective optimization.
Step 1: Formulate the problem
Action:
Write constraints and an objective using (minimize ...) or
(maximize ...) directives, followed by (check-sat) and (get-model).
Expectation: A valid SMT-LIB2 formula with at least one optimization directive and all variables declared.
Result: If the formula is well-formed, proceed to Step 2. For multi-objective problems, list directives in priority order for lexicographic optimization.
Example: minimize x + y subject to x >= 1, y >= 2, x + y <= 10:
(declare-const x Int)
(declare-const y Int)
(assert (>= x 1))
(assert (>= y 2))
(assert (<= (+ x y) 10))
(minimize (+ x y))
(check-sat)
(get-model)
Step 2: Run the optimizer
Action: Invoke optimize.py with the formula or file path.
Expectation:
The script prints sat with the optimal assignment, unsat, unknown,
or timeout. A run entry is logged to z3agent.db.
Result:
On sat: proceed to Step 3 to read the optimal values.
On unsat or timeout: check constraints for contradictions or simplify.
python3 scripts/optimize.py --file scheduling.smt2
python3 scripts/optimize.py --formula "<inline smt-lib2>" --debug
Step 3: Interpret the output
Action: Parse the objective value and satisfying assignment from the output.
Expectation:
sat with a model containing the optimal value, unsat indicating
infeasibility, or unknown/timeout.
Result:
On sat: report the optimal value and assignment.
On unsat: the constraints are contradictory, no feasible solution exists.
On unknown/timeout: relax constraints or try simplify.
Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| formula | string | no | SMT-LIB2 formula with minimize/maximize | |
| file | path | no | path to .smt2 file | |
| timeout | int | no | 60 | seconds |
| z3 | path | no | auto | path to z3 binary |
| debug | flag | no | off | verbose tracing |
| db | path | no | .z3-agent/z3agent.db | logging database |