rvt 0.4.0

Apache-2.0 clean-room reader for Autodesk Revit files (.rvt, .rfa, .rte, .rft) without Revit: metadata, previews and the embedded schema of 2016-2026 files, and typed elements with measured geometry from Revit 2024 and 2025 projects, exported as IFC4, glTF and plan SVG.
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# Element decoder template

A [`cargo-generate`](https://cargo-generate.github.io/cargo-generate/)
template for scaffolding a new per-class element decoder under
`src/elements/`.

Adding a decoder for a Revit class is always the same three-file
change (register in `mod.rs`, implement the decoder, add tests). This
template generates the decoder file + test module so you can focus on
the fields that are actually class-specific.

## Usage

From the repo root:

```sh
cargo install cargo-generate       # one-time
cargo generate --path templates/element-decoder --name dimension
```

`--name` is informational — cargo-generate uses it as the generated
project name but it does not control the output file. What controls
the output file is the `class_name` prompt: the template lands at
`src/elements/<snake_case_of_class_name>.rs`.

### Prompts

| Prompt | What to type | Example |
|---|---|---|
| `class_name` | Revit class name in PascalCase | `Dimension` |
| `struct_description` | One-line description for the module docstring | `Revit's dimension annotation element (linear, radial, angular, arc-length).` |
| `class_name_snake` | Auto-derived, press enter to accept | `dimension` |

Only `class_name` and `struct_description` need manual input — the
snake-case form is derived from `class_name` via the liquid
`snake_case` filter.

## After generation

The generated file compiles as-is (it builds a minimal
`simple_decoder!` + `{{class_name}}` struct with a single `name`
field) but it is a **scaffold**, not a finished decoder. Three
follow-up steps:

1. **Register it** in `src/elements/mod.rs`:

   ```rust
   pub mod dimension;

   pub fn all_decoders() -> Vec<Box<dyn ElementDecoder>> {
       vec![
           // ... existing decoders
           Box::new(dimension::DimensionDecoder),
       ]
   }
   ```

2. **Fill in the fields.** Dump the schema from a known-good fixture
   with `cargo run --release --bin rvt-schema -- _corpus/<file>.rfa`
   and record the real field list in the module docstring + the
   typed struct. Replace the `TODO` markers left by the template.

3. **Extend the tests.** The template ships three canonical tests
   (`<snake>_rejects_wrong_schema`, `<snake>_from_decoded`,
   `empty_tolerance`) that exercise the name field. Add more tests
   once the full field shape is known — see
   `src/elements/level.rs` and `src/elements/drafting.rs` for
   fuller examples.

The contributor guide at `docs/extending-layer-5b.md` has the full
walkthrough including field-type dispatch, schema discovery, and
corpus integration tests.

## Style notes

- Generated files follow `drafting.rs` conventions: 4-space indent,
  `simple_decoder!` macro, `normalise_field_name` imported from the
  `level` module, tests using `ClassEntry { ..., was_parent_only:
  false, ancestor_tag: None }`.
- `cargo fmt --all` and `cargo clippy --all-targets -- -D warnings`
  must both be clean after you finish populating the decoder — the
  scaffold already passes both gates.
- Do not delete the `TODO` markers without replacing them with real
  content; the guide grep's for them to find decoders that were
  scaffolded but never filled in.