# Modeling Workflows

## Modeling Mental Model

- Model the part as a sequence of intentional operations, not as one opaque final shape.
- Use the standard parts library first when a requested standard component is available and does not need complex custom geometry changes.
- Start from profiles and reference geometry, then create solids with features such as extrude, revolve, loft, and sweep.
- Use booleans and detail features after the base form is clear: cut openings, union intended merged bodies, then apply fillets, chamfers, or shell operations.
- Use `@scad.model` for a top-level replayable entry point. It owns one `GraphSession` and returns a `ModelResult`; use `@scad.requires_session` for child builders.
- Use QL for grounding and selection. Query the facts you need, such as face normals, centers, areas, edge lengths, curve types, and tags.
- Use indexed child-geometry getters such as `get_edges(index)` and `get_faces(index)` when an indexed topology pick is intentional.
- Use semantic tags for design intent and anchors. Keep numeric measurements and geometry facts in metadata or model JSON payloads.
- Treat `ModelResult.model_json` as the interchange boundary for new model entry points. Use `export_model_json(session=...)` for lower-level direct sessions.
- Declare directly controlled dimensions with `var(..., unit=..., tolerance=..., tolerance_unit=...)`, and attach derived requirements with `GraphSession.require_tolerance(...)` when manufacturing variation matters.
- Validate incrementally: after each major step, print small QL-derived facts such as selected face count, top face center, edge count, volume, or replay result count.

## 1) Capture a replayable modeling flow

```python
import simplecadapi as scad

@scad.model(graph_id="bracket")
def build_bracket():
    body = scad.make_box_rsolid(width=20.0, height=10.0, depth=3.0)
    scad.capture_result(value=body)
    return body

result = build_bracket()
payload = result.model_json
rebuilt = result.replay()
```

## 2) Import and use in Python

```python
import simplecadapi as scad
```

## 3) Keep replay payloads as the interchange boundary

- Prefer `export_model_json()` output instead of hand-written payloads.
- Use `ModelResult.replay()` for a model invocation, or `replay_model_json(json_str=...)` when consuming standalone model JSON.
- Use `import_model_json()` when consuming previously exported payloads.

## 4) Use standard parts when they fit

```python
import simplecadapi as scad

gear = scad.std.gear.make_spur_gear_rsolid(
    n_teeth=24,
    module=1.5,
    gear_height=8.0,
)
rack = scad.std.gear.make_spur_rack_rsolid(module=1.5, n_teeth=18)
bearing = scad.std.bearing.make_ball_bearing_rassembly(
    bore_diameter=8.0,
    outer_diameter=22.0,
    bearing_width=7.0,
    ball_diameter=3.5,
)
```

- Read `references/docs/stdlib/README.md` before hand-modeling a standard mechanical part.
- Use `references/docs/stdlib/<function_name>.md` for exact standard-library signatures.
- Continue with core geometry APIs when the standard part requires substantial custom geometry beyond the provided parameters.

## 5) QL-grounded feature workflow

```python
import simplecadapi as scad
from simplecadapi import ql

@scad.model(graph_id="swept_profile")
def build_model():
    profile = scad.make_circle_rface(center=(0, 0, 0), radius=1.0)
    body = scad.extrude_rsolid(
        profile=profile,
        direction=(0, 0, 1),
        distance=4.0,
        end_face_tag="role.sweep_profile",
        result_tag="part.body",
    )
    end_face = (
        ql.faces()
        .where(ql.output_role(role_name="extrusion.end"))
        .exactly(1)
        .resolve(body)[0]
    )
    print("end face center", end_face.get_center())
    path = scad.make_segment_rwire(start=(0, 0, 4), end=(0, 0, 8))
    swept = scad.sweep_rsolid(profile=end_face, path=path)
    scad.capture_result(value=swept)
    return swept

result = build_model()
rebuilt = result.replay()
print("rebuilt", len(rebuilt))
```

## 6) Selection and tag discipline

- Prefer QL selectors for semantic/geometric feature input selection.
- Use `get_edges(index)`, `get_faces(index)`, `get_wires(index)`, or `get_vertices(index)` for intentional indexed picks in examples.
- Attach local semantic tags with `apply_tag(shape=..., tag=...)`. Use `apply_tag_rselection(...)` for selector targets, explicit downward inheritance, or immutable semantic branches.
- Inspect with `list_tags(shape=..., scope=...)` and `explain_tag(...)`; `effective` excludes `lineage`.
- Use tags for topology identity, intent, roles, anchors, and groups.
- Store dimensions, positions, measured geometry, operation events, source roles, and descriptive payloads in metadata or model JSON, not in tags.
- Keep QL result prints concise: selected count, centers, normals, areas, lengths, or tags.

## 7) Kernel-proven feature output roles

- Feature output roles are typed tracking evidence, not user tag strings. Query them with `ql.output_role(role_name=...)`.
- The feature APIs expose one named tag argument per output role. Every requested role is strict: `one` roles require exactly one proven target, and `many` roles require at least one and tag the full proven set.
- There is no generic role-to-tag mapping. Unknown or unavailable roles and non-normalized tags fail before returning geometry.
- `result_tag` targets the one result Solid. Role tags target Faces except for `shell.wall`, which targets Edges.
- `tag_prefix` creates topology-identity tags such as `body.face.side.right`; role-specific tag parameters and `result_tag` create tags such as `role.mounting_surface` and `part.body`. They share one tag API, while their evidence and projection policies differ. Tag text alone never establishes topology identity.
- Box exposes the exact `box.bottom`, `box.top`, `box.front`, `box.back`, `box.left`, and `box.right` Face roles. It does not expose Edge roles; use tagged incident Faces with QL `incident_to(...)` or `shared_boundary(...)` for exact Box Edge selection.
- Cone exposes `cone.start`, optional `cone.end`, and `cone.side` Face roles plus `cone.start_boundary`, `cone.end_boundary`, and `cone.seam` Edge roles. A pointed cone has no end cap Face, but its end boundary is retained as the kernel's degenerate apex Edge.
- A 360-degree revolve has no distinct start/end caps. Requesting those tags fails rather than inventing cap roles.
- Shell role availability follows actual OCC evidence. For example, an operation may prove offset faces, closing descendants, and wall edges without proving a `shell.body_face` set.
- Sweep currently rejects a profile with inner wires rather than silently sweeping only its outer wire.

```python
body = scad.extrude_rsolid(
    profile=profile,
    direction=(0, 0, 1),
    distance=10.0,
    start_face_tag="anchor.base",
    end_face_tag="role.mounting_surface",
    side_faces_tag="group.outer_walls",
    result_tag="part.body",
)

mounting_face = (
    ql.faces()
    .where(ql.output_role(role_name="extrusion.end"))
    .exactly(1)
    .resolve(body)[0]
)
print(scad.list_tags(shape=mounting_face, scope="local"))
```

In a `GraphSession`, each requested assignment becomes a canonical
`apply_tag_rselection` semantic node. The feature node remains geometry-only, and
replay validates both the recomputed role set and the exact selected refs.

## 8) Replay-safe source projection

When a feature supports source projection, keep the returned semantic view in the
feature's input chain:

```python
profile = scad.make_rectangle_rface(width=5.0, height=3.0)
source_edge = profile.get_edges(0)
profile = scad.apply_tag_rselection(
    scope=profile,
    targets=[source_edge],
    tag="role.source_edge",
)
source_edge = scad.select_edges_by_tag(
    shape=profile,
    tag="role.source_edge",
    scope="local",
)[0]
source_binding_id = scad.explain_tag(
    shape=source_edge,
    tag="role.source_edge",
    scope="local",
)[0]["binding_id"]

body = scad.extrude_rsolid(
    profile=profile,
    direction=(0, 0, 1),
    distance=2.0,
)
projected_face = (
    ql.faces()
    .where(ql.source_binding(binding_id=source_binding_id))
    .exactly(1)
    .resolve(body)[0]
)
print(scad.list_tags(shape=projected_face, scope="local"))
```

The projected binding preserves the exact source binding ID, source topology ID,
target topology ID, operation, role, and evidence method. `ql.source_binding(...)`
and `ql.source_topology(...)` inspect this local evidence. They do not search tag
text or infer ancestry from geometry. Calling `apply_tag_rselection(...)` but then
passing the original profile to the feature creates a detached semantic branch and
does not authorize hidden coupling.

## 9) Constrained Sketch topology tags

- Give every profile entity a stable explicit `entity_id` when constructing a constrained Sketch.
- Promote through `make_wire_from_sketch_rwire(...)` or `make_face_from_sketch_rface(...)`; the promotion map is the exact entity-to-Edge correspondence.
- Inspect canonical topology-identity tags with `ql.tag("sketch.rect.entity.right")` or `explain_tag(...)`; the evidence contains `topology_name` and `SketchPromotionMap`.
- A promoted profile receives `sketch.<sketch-name>.profile.<profile-id>` and each boundary Edge receives `sketch.<sketch-name>.entity.<entity-id>`.
- If the generated Edge count differs from the promotion map, fail rather than guessing correspondence.
- A feature can project a Sketch entity topology tag only when kernel history proves one source Edge to one result Face.

## 10) Boolean and body discipline

- Use `union_rsolid(...)` when multiple solids should become one integrated body.
- Ensure bodies that should union into one solid have real geometric overlap or embedding.
- Use `cut_rsolid(...)` for subtractive features and `intersect_rsolid(...)` for common-volume workflows.
- Validate body count and volume after major boolean operations.

## 11) Dimension tolerance chains

```python
width = scad.var("width", 10.0, unit="mm", tolerance=0.1)
gap = scad.var("gap", 0.5, unit="mm", tolerance=(-0.05, 0.1))
overall = width + gap

with scad.GraphSession() as session:
    body = scad.make_box_rsolid(width, 2.0, 1.0)
    session.require_tolerance(overall, (-0.15, 0.2), tolerance_unit="mm", name="overall")

report = session.validate_tolerances(raise_on_failure=True)
```

- Use `worst_case` for a guaranteed conservative envelope.
- Use `rss` only when distinct source dimensions can be treated as independent.
- Every source variable in a chain must have a declared tolerance.
- Unit-aware expressions infer dimensions automatically and cannot mix legacy
  variables without units.
- Length and angle use canonical `mm` and `deg` values in CAD operations.
- Read `references/docs/core/physical-units.md` for unit and inference rules.
- Read `references/docs/core/dimension-tolerance-chains.md` for complete rules.