القائمة
Check satisfiability of SMT-LIB2 formulas using Z3. Returns sat/unsat with models or unsat cores. Logs every invocation to z3agent.db for auditability.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Conversational skill that interviews users to design new agentic workflows
Route gh-aw workflow design/create/debug/upgrade requests to the right prompts.
Run AddressSanitizer and UndefinedBehaviorSanitizer on the Z3 test suite to detect memory errors, undefined behavior, and leaks. Logs each finding to z3agent.db.
Run Clang Static Analyzer (scan-build) on Z3 source and log structured findings to z3agent.db.
Measure Z3 performance on a formula or file. Collects wall-clock time, theory solver statistics, memory usage, and conflict counts. Results are logged to z3agent.db for longitudinal tracking.
Translate constraint problems into SMT-LIB2 or Z3 Python API code. Handles common problem classes including scheduling, graph coloring, arithmetic puzzles, and verification conditions.
| name | solve |
| description | Check satisfiability of SMT-LIB2 formulas using Z3. Returns sat/unsat with models or unsat cores. Logs every invocation to z3agent.db for auditability. |
Given an SMT-LIB2 formula (or a set of constraints described in natural language), determine whether the formula is satisfiable. If sat, extract a satisfying assignment. If unsat and tracking labels are present, extract the unsat core.
Action: Convert the input to valid SMT-LIB2. If the input is natural language, use the encode skill first.
Expectation:
A syntactically valid SMT-LIB2 formula ending with (check-sat) and
either (get-model) or (get-unsat-core) as appropriate.
Result: If valid SMT-LIB2 is ready, proceed to Step 2. If encoding is needed, run encode first and return here.
Action: Invoke solve.py with the formula string or file path.
Expectation:
The script pipes the formula to z3 -in, logs the run to
.z3-agent/z3agent.db, and prints the result.
Result:
Output is one of sat, unsat, unknown, or timeout.
Proceed to Step 3 to interpret.
python3 scripts/solve.py --formula "(declare-const x Int)(assert (> x 0))(check-sat)(get-model)"
For file input:
python3 scripts/solve.py --file problem.smt2
With debug tracing:
python3 scripts/solve.py --file problem.smt2 --debug
Action: Parse the Z3 output to determine satisfiability and extract any model or unsat core.
Expectation:
sat with a model, unsat optionally with a core, unknown, or
timeout.
Result:
On sat: report the model to the user.
On unsat: report the core if available.
On unknown/timeout: try simplify or increase the timeout.
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| formula | string | no | SMT-LIB2 formula as a string | |
| file | path | no | path to an .smt2 file | |
| timeout | int | no | 30 | seconds before killing z3 |
| z3 | path | no | auto | explicit path to z3 binary |
| debug | flag | no | off | print z3 command, stdin, stdout, stderr, timing |
| db | path | no | .z3-agent/z3agent.db | path to the logging database |
Either formula or file must be provided.