let domains author their own pass-2 estimator as formulas, not Python

Pass 2 previously only knew one estimator: a hardcoded physics model that
matches dimensions literally named platform/actuator/energy_storage. Any
domain outside that shape (e.g. archery) got all-zero estimates and failed
every combo. Domains can now declare free variables and per-metric formulas
as data instead; a safe AST-based evaluator (engine/formula.py, no eval())
resolves declared entity properties via dep(key, constraint_type) and
generalizes the existing hand-nested mass-budget search into an N-variable
recursive optimizer. Fully additive -- the legacy platform/actuator/
energy_storage path is untouched and still runs unchanged for every domain
that declares no formulas.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

tests/test_repository.py

@@ -1,7 +1,7 @@
 """Tests for the database repository."""
 
 from physcom.models.entity import Entity, Dependency
-from physcom.models.domain import Domain, MetricBound
+from physcom.models.domain import Domain, FreeVariable, MetricBound, MetricFormula
 
 
 def test_ensure_dimension(repo):
@@ -63,6 +63,62 @@ def test_add_and_get_domain(repo):
     assert loaded.metric_bounds[0].metric_name == "speed"
 
 
+def test_add_domain_with_free_variables_and_formulas(repo):
+    domain = Domain(
+        name="archery_test",
+        metric_bounds=[MetricBound("drawback_force", weight=1.0, norm_min=0, norm_max=500)],
+        free_variables=[
+            FreeVariable(
+                name="draw_weight",
+                floor_formula='dep("draw_weight", "range_min")',
+                ceiling_formula='dep("draw_weight", "range_max")',
+                sort_order=0,
+            ),
+        ],
+        metric_formulas=[
+            MetricFormula(metric_name="drawback_force", formula="draw_weight * 1.5"),
+        ],
+    )
+    saved = repo.add_domain(domain)
+    assert saved.id is not None
+
+    loaded = repo.get_domain("archery_test")
+    assert loaded is not None
+    assert len(loaded.free_variables) == 1
+    assert loaded.free_variables[0].name == "draw_weight"
+    assert loaded.free_variables[0].id is not None
+    assert len(loaded.metric_formulas) == 1
+    assert loaded.metric_formulas[0].formula == "draw_weight * 1.5"
+
+
+def test_free_variable_and_formula_crud(repo):
+    domain = repo.add_domain(Domain(name="crud_test"))
+
+    fv = repo.add_free_variable(
+        domain.id,
+        FreeVariable(name="x", floor_formula="0", ceiling_formula="100", sort_order=0),
+    )
+    mf = repo.add_metric_formula(
+        domain.id, MetricFormula(metric_name="m", formula="x * 2")
+    )
+
+    repo.update_free_variable(
+        fv.id, FreeVariable(name="x", floor_formula="1", ceiling_formula="200", sort_order=0)
+    )
+    repo.update_metric_formula(mf.id, MetricFormula(metric_name="m", formula="x * 3"))
+
+    loaded = repo.get_domain_by_id(domain.id)
+    assert loaded.free_variables[0].floor_formula == "1"
+    assert loaded.free_variables[0].ceiling_formula == "200"
+    assert loaded.metric_formulas[0].formula == "x * 3"
+
+    repo.delete_free_variable(fv.id)
+    repo.delete_metric_formula(mf.id)
+    loaded = repo.get_domain_by_id(domain.id)
+    assert loaded.free_variables == []
+    assert loaded.metric_formulas == []
+
+
 def test_combination_save_and_dedup(repo):
     e1 = repo.add_entity(Entity(name="A", dimension="platform"))
     e2 = repo.add_entity(Entity(name="B", dimension="actuator"))