diff --git a/.github/workflows/check_python_package.yaml b/.github/workflows/check_python_package.yaml
new file mode 100644
index 0000000..5bd82ab
--- /dev/null
+++ b/.github/workflows/check_python_package.yaml
@@ -0,0 +1,33 @@
+name: Check
+
+on:
+  push:
+  pull_request:
+    branches: ["main"]
+
+jobs:
+  test:
+    strategy:
+      fail-fast: false
+      matrix:
+        runs-on: [ubuntu-latest, macos-latest, windows-latest]
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
+    runs-on: ${{matrix.runs-on}}
+    steps:
+      - uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v7
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install the project
+        run: uv sync --all-extras --dev
+
+      - name: Lint with ruff
+        run: uv run ruff check --output-format=github .
+
+      - name: Run tests
+        run: uv run pytest --cov=opltools --cov-report=term-missing
diff --git a/SCHEMA.md b/SCHEMA.md
new file mode 100644
index 0000000..ae9c18b
--- /dev/null
+++ b/SCHEMA.md
@@ -0,0 +1,305 @@
+# OPL Schema
+
+The OPL schema catalogs optimization **problems**, **suites**, **generators**, and their **implementations** in a single, machine-readable format. 
+
+Three design choices shape everything below:
+
+1. **One flat library, keyed by ID.** 
+   Every entity lives in a `Library` dict. 
+   Suites reference problems, problems reference implementations using their respective ID.
+   There is no embedding of problems or implementations within suites to facilitate reuse. 
+   F.e. an implementation might be referenced by multiple problems or suites.
+2. **Numeric fields accept a scalar, a set, or a range.** 
+   A problem may have exactly `2` objectives, one of `{2, 3, 5}`, or any value in `{min: 2, max: 50}`. 
+   The same union type is used for variable dimensions and constraint counts.
+3. **Three-valued logic for yes/no fields.** 
+   Many boolean fields (f.e. `hard`, `allows_partial_evaluation`, ...) [`YesNoSome`](#yesnosome) as their value.
+   We lose some expressive power but simplify the data entry.
+   If we force authors to decide on yes or no, then we would need more complex structures for variables, constraints etc. and that would make the usual case unnecessarily complex.
+   
+## Contents
+
+- [Library](#library) 
+- [Thing types](#thing-types)
+  - [Implementation](#implementation)
+  - [ProblemLike](#problemlike) (shared fields)
+    - [Problem](#problem)
+    - [Suite](#suite)
+    - [Generator](#generator)
+- [Shared building blocks](#shared-building-blocks)
+  - [Variable](#variable) / [VariableType](#variabletype)
+  - [Constraint](#constraint) / [ConstraintType](#constrainttype)
+  - [Reference](#reference) / [Link](#link)
+  - [ValueRange](#valuerange)
+  - [YesNoSome](#yesnosome)
+
+---
+
+## Library
+
+A `Library` is a dict from ID to a [Thing](#thing-types).
+IDs are free-form but must be unique and the convention is to add a prefix marking the type to avoid collisions:
+
+| Prefix  | Type             |
+|---------|------------------|
+| `impl_` | Implementation   |
+| `fn_`   | Problem          |
+| `suite_`| Suite            |
+| `gen_`  | Generator        |
+
+On load the library validates that every ID referenced by a suite (`problems`) or problem (`implementations`) exists and has the correct type. Suites also have their `fidelity_levels` auto-populated from their problems.
+
+```yaml
+impl_coco:
+  type: implementation
+  name: COCO
+  description: Comparing Continuous Optimisers
+fn_sphere:
+  type: problem
+  name: Sphere
+  objectives: [1]
+  implementations: [impl_coco]
+suite_bbob:
+  type: suite
+  name: BBOB
+  problems: [fn_sphere]
+```
+
+---
+
+## Thing types
+
+All entities inherit from `Thing`, which only carries a discriminator:
+
+```yaml
+type: problem  # or: suite | generator | implementation
+```
+
+We want to have as flat a structure as possible to make exploring and searching OPL as easy as possible. 
+That's one of the reasonst the top level object is a dictionary of dissimilar things.
+But we need to be able to tell them apart so we have a `type` field to discriminate between them.
+
+### Implementation
+
+A pointer to code that implements one or more problems. 
+Intentionally minimal so that the schema describes *what* a problem is, not how to run it.
+There are separate files which contain curated usage examples for problems or suites keyed by their respective IDs.
+
+| Field             | Type                              | Notes                                        |
+|-------------------|-----------------------------------|----------------------------------------------|
+| `name`            | str                               | required                                     |
+| `description`     | str                               | required                                     |
+| `language`        | str? (e.g. `python`, `c`)         |                                              |
+| `links`           | list of [Link](#link)?            | repo, release, docs…                         |
+| `evaluation_time` | set of str?                       | free-form list ("8 minutes", "fast")         |
+| `requirements`    | str or list of str?               | URL to requirements file or list of packages |
+
+```yaml
+impl_coco:
+  type: implementation
+  name: COCO
+  description: Comparing Continuous Optimisers benchmarking platform
+  language: c
+  links:
+    - {type: repository, url: https://github.com/numbbo/coco-experiment}
+impl_py_cocoex:
+  type: implementation
+  name: Python bindings for COCO
+  description: The Python bindings for the experimental part of the COCO framework
+  language: Python
+  links:
+    - {type: source, url: https://github.com/numbbo/coco-experiment/tree/main/build/python}
+    - {type: package, url: https://pypi.org/project/coco-experiment/}
+```
+
+### ProblemLike
+
+Fields shared by [Problem](#problem), [Suite](#suite), and [Generator](#generator). 
+The schema deliberately puts most descriptive fields here so suites can be characterised without explicitly having to add all problems in the suite.
+
+| Field                                    | Type                                           | Notes                                              |
+|------------------------------------------|------------------------------------------------|----------------------------------------------------|
+| `name`                                   | str                                            | required                                           |
+| `long_name`                              | str?                                           |                                                    |
+| `description`                            | str? (markdown)                                | longer prose                                       |
+| `tags`                                   | set of str?                                    | free-form keywords                                 |
+| `references`                             | set of [Reference](#reference)?                |                                                    |
+| `implementations`                        | set of IDs?                                    | must resolve to [Implementation](#implementation)s |
+| `objectives`                             | set of int?                                    | e.g. `{1}`, `{2, 3}` — **not** a ValueRange        |
+| `variables`                              | set of [Variable](#variable)?                  |                                                    |
+| `constraints`                            | set of [Constraint](#constraint)?              | omit entirely for unconstrained                    |
+| `dynamic_type`                           | set of str?                                    | `{"no"}`, `{"time-varying"}`…                      |
+| `noise_type`                             | set of str?                                    | `{"none"}`, `{"gaussian"}`…                        |
+| `allows_partial_evaluation`              | [YesNoSome](#yesnosome)?                       |                                                    |
+| `can_evaluate_objectives_independently`  | [YesNoSome](#yesnosome)?                       |                                                    |
+| `modality`                               | set of str?                                    | `{"unimodal"}`, `{"multimodal"}`                   |
+| `fidelity_levels`                        | set of int?                                    | `{1}` = single-fidelity, `{1,2}` = multi-fidelity  |
+| `code_examples`                          | set of str?                                    | paths to example scripts                           |
+| `evaluation_time`                        | set of str?                                    | free-form list ("8 minutes", "fast")         |
+| `source`                                 | set of str?                                    | `{"artificial"}`, `{"real-world"}`                 |
+
+> `objectives` is a set of integers because we don't assume extreme scalability in this property so explicit enumeration is fine.
+> Dimensions of variables on the other hand are ranges because here problems often are scalable over wide ranges.
+
+When no `evaluation_time` is set, it percolates up from any referenced implementations.
+The same is true for the `variables` and `constraints` properties of a suite that has references to problems.
+
+### Problem
+
+One optimization problem (possibly parameterised by instances).
+
+Adds:
+
+| Field       | Type                                       | Notes                                      |
+|-------------|--------------------------------------------|--------------------------------------------|
+| `instances` | [ValueRange](#valuerange) or list of str?  | e.g. `{min: 1, max: 15}` or named variants |
+
+```yaml
+fn_sphere:
+  type: problem
+  name: Sphere
+  objectives: [1]
+  variables: [{type: continuous, dim: {min: 2, max: 40}}]
+  modality: [unimodal]
+  source: [artificial]
+  instances: {min: 1, max: 15}
+  implementations: [impl_coco]
+```
+
+### Suite
+
+A curated, fixed collection of problems.
+
+Adds:
+
+| Field      | Type         | Notes                                         |
+|------------|--------------|-----------------------------------------------|
+| `problems` | set of IDs?  | must resolve to [Problem](#problem)s          |
+
+`fidelity_levels` is auto-unioned from member problems at validation time.
+
+```yaml
+suite_bbob:
+  type: suite
+  name: BBOB
+  problems: [fn_sphere, fn_rosenbrock, fn_rastrigin]
+  objectives: [1]
+  source: [artificial]
+  implementations: [impl_coco]
+```
+
+### Generator
+
+A parametric family of problems — unlike a [Suite](#suite), the member problems are not enumerated. Uses the same fields as [ProblemLike](#problemlike) with no additions; the distinction from [Problem](#problem) is that a generator produces instances on demand.
+
+```yaml
+gen_mpm2:
+  type: generator
+  name: MPM2
+  description: Multiple peaks model, second instantiation
+  objectives: [1]
+  variables: [{type: continuous, dim: {min: 1}}]
+  modality: [multimodal]
+```
+
+---
+
+## Shared building blocks
+
+### Variable
+
+A group of decision variables of the same type. 
+Multi-type problems list multiple entries.
+While you can have multiple entries of the same type, this should be justified in some way like when you can evaluate the problem on only one subset of variables.
+
+| Field  | Type                                          | Default              |
+|--------|-----------------------------------------------|----------------------|
+| `type` | [VariableType](#variabletype)                 | `unknown`            |
+| `dim`  | int, set of int, [ValueRange](#valuerange), or null | `0`            |
+
+```yaml
+variables:
+  - {type: continuous, dim: 10}
+  - {type: integer, dim: {min: 1, max: 5}}
+```
+
+### VariableType
+
+`continuous | integer | binary | categorical | unknown`. 
+Use `unknown` for permutation/combinatorial problems the schema doesn't yet distinguish **and** add an appropriate tag.
+We are actively watching for unknown variable types and are open to extending the above list if there is a critical mass of problems to justify it.
+
+### Constraint
+
+A group of constraints. 
+To indicate that the problem is unconstrained, you need an _empty_ `constraints` field.
+A missing `constraints` field or if it is set to `null` means it is not known if unconstrained.
+
+| Field      | Type                                          | Notes                              |
+|------------|-----------------------------------------------|------------------------------------|
+| `type`     | [ConstraintType](#constrainttype)             | default `unknown`                  |
+| `hard`     | [YesNoSome](#yesnosome)?                      | hard vs. soft                      |
+| `equality` | [YesNoSome](#yesnosome)?                      | equality vs. inequality            |
+| `number`   | int, set of int, [ValueRange](#valuerange), null |                                 |
+
+```yaml
+constraints:
+  - {type: box, hard: yes, number: 10}
+  - {type: linear, hard: some, equality: no, number: {min: 1}}
+```
+
+### ConstraintType
+
+`box | linear | function | unknown`. `function` covers non-linear/black-box constraints.
+
+### Reference
+
+Bibliographic pointer. 
+Requires either a `title` or a `link` and optionally a list of  `authors`.
+
+```yaml
+references:
+  - title: "Honey Badger Algorithm: New metaheuristic algorithm for solving optimization problems."
+    authors: 
+      - Fatma A. Hashim
+      - Essam H. Houssein
+      - Kashif Hussain
+      - Mai S. Mabrouk
+      - Walid Al-Atabany      
+    link: {type: doi, url: "https://doi.org/10.1016/j.matcom.2021.08.013"]
+```
+
+### Link
+
+`{type?: str, url: str}`. 
+`type` is free-form (`repository`, `arxiv`, `paper`, `doi`, ...).
+`url` is a URL to some resource. 
+
+If `type` is `doi`, please use the full URL (starting with `https://doi.org/...`) instead of the raw DOI.
+
+### ValueRange
+
+An inclusive numeric range type. 
+At least one of `min`/`max` must be given.
+If `min` is given and `max` is missing, it does not imply that there is no upper bound. 
+There might be one, it is just not known.
+The same applies for the case where `max` is given and `min` is missing.
+
+```yaml
+dim: {min: 2}            # 2 or more
+dim: {min: 2, max: 40}   # between 2 and 40
+dim: {max: 100}          # up to 100
+```
+
+Used by `Variable.dim`, `Constraint.number`, `Problem.instances`.
+
+### YesNoSome
+
+Three-valued flag: `yes | no | some | ?` (the last serialises as the literal `'?'` string, meaning unknown).
+`some` captures the common case where *part* of something has some property.
+For example only some constraints might hard but we don't know the exact number of hard and soft constraints, only the total number.
+
+```yaml
+constraints: [{type: box, hard: some}]
+allows_partial_evaluation: "?"
+```
diff --git a/examples/cobi.py b/examples/cobi.py
new file mode 100644
index 0000000..2e534e4
--- /dev/null
+++ b/examples/cobi.py
@@ -0,0 +1,62 @@
+from opltools import Implementation, Generator, Reference, Library, Variable, Constraint
+from pydantic_yaml import to_yaml_str
+
+things = {}
+
+things["cobi_impl"] = Implementation(
+    name="COBI Implementation",
+    description="Python library for COBI (COnstrained BI-objective optimization) problem generator",
+    language="python",
+    links=[
+        {
+            "type": "repository",
+            "url": "https://github.com/numbbo/cobi-problem-generator/",
+        },
+        {
+            "type": "v0.5.0",
+            "url": "https://github.com/numbbo/cobi-problem-generator/releases/tag/v0.5.0",
+        },
+    ],
+    requirements="https://github.com/numbbo/cobi-problem-generator/blob/main/requirements.txt",
+)
+
+things["cobi_problem"] = Generator(
+    name="COBI Problem",
+    description="Generator of COnstrained BI-objective optimization problems",
+    tags={
+        "constrained",
+        "bi-objective",
+        "continuous",
+        "black-box",
+        "location",
+        "multi-peak",
+        "convex-quadratic",
+    },
+    references=[
+        Reference(
+            title="Pareto Set Characterization in Constrained Multiobjective Optimization and the COBI Problem Generator",
+            authors=["Anne Auger", "Dimo Brockhoff", "Luka Opravš", "Tea Tušar"],
+            link={"type": "arxiv", "url": "https://arxiv.org/abs/2604.09131"},
+        )
+    ],
+    objectives={2},
+    variables=[Variable(type="continuous", dim={"min": 1})],
+    implementations={"cobi_impl"},
+    can_evaluate_objectives_independently="no",
+    constraints=[
+        # FIXME: Check
+        Constraint(type="box", hard="yes", number={"min": 1}),
+        Constraint(type="linear", hard="yes", number={"min": 1}),
+        Constraint(type="function", hard="yes", number={"min": 1}),
+    ],
+    noise_type={"none"},
+    dynamic_type=None,
+    allows_partial_evaluation="no",
+    modality={"multi-modal per objective"},
+    fidelity_levels={1},
+    source={"artificial"},
+    code_examples={"./code_153.py"},
+)
+library = Library(things)
+
+print(to_yaml_str(library))
diff --git a/examples/demo.py b/examples/demo.py
new file mode 100644
index 0000000..0b866c2
--- /dev/null
+++ b/examples/demo.py
@@ -0,0 +1,35 @@
+from opltools import Suite, Problem, Library, Link, Variable, ValueRange
+from pydantic_yaml import to_yaml_str
+from opltools.schema import Implementation
+
+things = {}
+
+things["impl_py_cocoex"] = Implementation(
+    name="coco-experiment Python module",
+    description="Python bindings for the experiment part of the COCO framework",
+    language="python",
+    links=[
+        Link(type="repository", url="https://github.com/numbbo/coco-experiment"),
+        Link(type="package", url="https://pypi.org/project/coco-experiment/"),
+    ],
+    evaluation_time="sub second",
+)
+
+for fnr in range(1, 25):
+    id = f"fn_bbob_f{fnr}"
+    things[f"fn_bbob_f{fnr}"] = Problem(
+        name=f"BBOB F_{fnr}",
+        objectives={1},
+        variables={Variable(type="continuous", dim=ValueRange(min=1, max=80))},
+        implementations=["impl_py_cocoex"],
+    )
+
+things["suite_bbob"] = Suite(
+    name="BBOB",
+    problems={f"fn_bbob_f{fnr}" for fnr in range(1, 25)},
+    implementations=["impl_py_cocoex"],
+)
+
+library = Library(things)
+
+print(to_yaml_str(library))
diff --git a/examples/emdo.py b/examples/emdo.py
new file mode 100644
index 0000000..7a4504d
--- /dev/null
+++ b/examples/emdo.py
@@ -0,0 +1,82 @@
+from opltools import Library, Problem, Implementation
+from pydantic_yaml import to_yaml_str
+
+#! - name: Electric Motor Design Optimization
+#!   suite/generator/single: Single Problem
+#!   variable type: Continuous, Integer
+#!   dimensionality: '13'
+#!   objectives: '1'
+#!   constraints: 'yes'
+#!   dynamic: 'no'
+#!   noise: 'yes'
+#!   multimodal: 'yes'
+#!   multi-fidelity: 'no'
+#!   source (real-world/artificial): Real-World Application
+#!   implementation: Implementation not freely available
+#!   textual description: The goal is to find a design of a synchronous electric motor
+#!     for power steering systems that minimizes costs and satisfies all constraints.
+#!   reference: https://dis.ijs.si/tea/Publications/Tusar23Multistep.pdf (paper in Slovene)
+#!   other info:
+#!     partial evaluations: 'no'
+#!     full name: Electric Motor Design Optimization
+#!     constraint properties: Hard Constraints, Soft Constraints, Box Constraints
+#!     number of constraints: '12'
+#!     description of multimodality: Constraints are multimodal
+#!     key challenges / characteristics: Time-consuming solution evaluation, highly-constrained
+#!       problem
+#!     scientific motivation: Challenging to find good solutions in a limited time
+#!     limitations: 'Unavailability, even if available, it wouldn''t be helpful to use
+#!       for benchmarking due taking a long time to evaluate a single solution '
+#!     implementation languages: Python
+#!     approximate evaluation time: 8 minutes
+#!     general: This is not an available problem, but could be interesting to show to
+#!       researchers which difficulties appear in real-world problems
+
+library = Library({
+    "impl_emdo":  Implementation(
+        name="Electric Motor Design Optimization",
+        description="Not publicly available",
+        language="python",
+        evaluation_time=["8 minutes"]
+    ),
+    "fn_emdo":  Problem(
+        name="Electric Motor Design Optimization",
+        description="""# Goal
+Find a design of a synchronous electric motor for power steering systems that minimizes costs and satisfies all constraints.
+
+# Motivation
+Challenging to find good solutions in a limited time
+
+# Key Challenges
+* Time-consuming solution evaluation,
+* highly-constrained problem
+* Constraints are multimodal
+
+This is not an available problem, but could be interesting to show to researchers which difficulties appear in real-world problems""",
+        objectives=[1],
+        variables=[
+            {"type": "continuous", "dim": {"min": None, "max": 13}},
+            {"type": "integer", "dim": {"min": None, "max": 13}},
+        ],
+        modality=["multimodal"],
+        allows_partial_evaluation="no",
+        constraints=[
+            {"type": "box", "hard": "some", "number": 12}
+        ],
+        dynamic_type=["no"],
+        noise_type=["yes"],
+        fidelity_levels=[1],
+        source=["real-world"],
+        references=[
+            {
+                "title": "A Multi-Step Evaluation Process in Electric Motor Design",
+                "lang": "sj",
+                "authors": ["Tea Tušar", "Peter Korošec", "Bogdan Filipič"],
+                "link": {"url": "https://dis.ijs.si/tea/Publications/Tusar23Multistep.pdf"}
+            }
+        ],
+        implementations=["impl_emdo"]
+    )
+})
+
+print(to_yaml_str(library))
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..9be5ec9
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,37 @@
+[project]
+name = "opltools"
+version = "0.1.0"
+description = "Tools to manage the Optimization Problem Library"
+readme = "README.md"
+authors = [
+    { name = "Olaf Mersmann", email = "olafm@p-value.net" }
+]
+requires-python = ">=3.10"
+dependencies = [
+    "pydantic>=2.13.3",
+    "pydantic-yaml>=1.6.0",
+    "pyyaml>=6.0.3",
+]
+
+[project.scripts]
+opl = "opltools.cli:main"
+
+[project.optional-dependencies]
+cli = [
+    "rich>=15.0.0",
+]
+
+[build-system]
+requires = ["uv_build>=0.11.7,<0.12.0"]
+build-backend = "uv_build"
+
+[dependency-groups]
+dev = [
+    "pytest>=9.0.3",
+    "pytest-cov>=7.1.0",
+    "ruff>=0.15.11",
+]
+
+[tool.ruff]
+# In addition to the standard set of exclusions, omit all tests, plus a specific file.
+extend-exclude = ["utils/*.py"]
diff --git a/src/opltools/__init__.py b/src/opltools/__init__.py
new file mode 100644
index 0000000..b959bf9
--- /dev/null
+++ b/src/opltools/__init__.py
@@ -0,0 +1,27 @@
+from .schema import (
+    Problem,
+    Suite,
+    Generator,
+    Implementation,
+    Library,
+    YesNoSome,
+    Link,
+    Reference,
+    Variable,
+    ValueRange,
+    Constraint,
+)
+
+__all__ = [
+    "Problem",
+    "Suite",
+    "Generator",
+    "Implementation",
+    "Library",
+    "YesNoSome",
+    "Link",
+    "Reference",
+    "Constraint",
+    "Variable",
+    "ValueRange",
+]
diff --git a/src/opltools/cli.py b/src/opltools/cli.py
new file mode 100644
index 0000000..4a35d92
--- /dev/null
+++ b/src/opltools/cli.py
@@ -0,0 +1,46 @@
+import sys
+import argparse
+from pydantic import ValidationError
+from pydantic_yaml import parse_yaml_raw_as
+
+from .schema import Library
+
+
+def cmd_validate(args):
+    try:
+        with open(args.file) as f:
+            raw = f.read()
+    except OSError as e:
+        print(f"Error reading file: {e}", file=sys.stderr)
+        return 1
+
+    try:
+        parse_yaml_raw_as(Library, raw)
+        print(f"{args.file}: OK")
+        return 0
+    except ValidationError as e:
+        for error in e.errors():
+            loc = (
+                " -> ".join(str(p) for p in error["loc"]) if error["loc"] else "(root)"
+            )
+            print(f"{args.file}: {loc}: {error['msg']}")
+        return 1
+
+
+def main():
+    parser = argparse.ArgumentParser(prog="opl", description="OPL tools")
+    subparsers = parser.add_subparsers(dest="command", required=True)
+
+    validate_parser = subparsers.add_parser(
+        "validate", help="Validate a YAML file against the Library schema"
+    )
+    validate_parser.add_argument("file", help="YAML file to validate")
+
+    args = parser.parse_args()
+
+    if args.command == "validate":
+        sys.exit(cmd_validate(args))
+
+
+if __name__ == "__main__":
+    main()
diff --git a/src/opltools/py.typed b/src/opltools/py.typed
new file mode 100644
index 0000000..e69de29
diff --git a/src/opltools/schema.py b/src/opltools/schema.py
new file mode 100644
index 0000000..a2c5b5b
--- /dev/null
+++ b/src/opltools/schema.py
@@ -0,0 +1,214 @@
+from enum import Enum
+from typing import Any
+from typing_extensions import Self
+from pydantic import BaseModel, RootModel, ConfigDict, model_validator
+
+from .yesnosome import YesNoSome
+from .utils import ValueRange, union_range
+
+
+class OPLType(Enum):
+    problem = "problem"
+    suite = "suite"
+    generator = "generator"
+    implementation = "implementation"
+
+
+class Link(BaseModel):
+    type: str | None = None
+    url: str
+
+    def __hash__(self):
+        return hash(self.type) + hash(self.url)
+
+
+class Thing(BaseModel):
+    type: OPLType
+    model_config = ConfigDict(extra="allow")
+
+
+class Objectives(RootModel):
+    root: int | set[int] | ValueRange = 0
+
+    def union(self, other: Self) -> Self:
+        self.root = union_range(self.root, other.root)
+        return self
+
+
+class VariableType(Enum):
+    continuous = "continuous"
+    integer = "integer"
+    binary = "binary"
+    categorical = "categorical"
+    unknown = "unknown"
+
+
+class Variable(BaseModel):
+    type: VariableType = VariableType.unknown
+    dim: int | set[int] | ValueRange | None = 0
+
+    def __hash__(self):
+        if isinstance(self.dim, set):
+            dim_hash = hash(frozenset(self.dim))
+        else:
+            dim_hash = hash(self.dim)
+        return hash(self.type) + dim_hash
+
+
+class ConstraintType(Enum):
+    box = "box"
+    linear = "linear"
+    function = "function"
+    unknown = "unknown"
+
+
+class Constraint(BaseModel):
+    type: ConstraintType = ConstraintType.unknown
+    hard: YesNoSome | None = None
+    equality: YesNoSome | None = None
+    number: int | set[int] | ValueRange | None = None
+
+    def __hash__(self):
+        number = frozenset(self.number) if isinstance(self.number, set) else self.number
+        return hash((self.type, self.hard, self.equality, number))
+
+
+class Reference(BaseModel):
+    title: str | None = None
+    authors: list[str] | None = None
+    link: Link | None = None
+
+    @model_validator(mode="after")
+    def _validate(self) -> Self:
+        if self.title is None and self.link is None:
+            raise ValueError("References must have either a title or a link.")
+        return self
+
+    def __hash__(self):
+        return hash(self.title) + hash(self.link)
+
+
+class Usage(BaseModel):
+    language: str
+    code: str
+
+
+class Implementation(Thing):
+    type: OPLType = OPLType.implementation
+    name: str
+    description: str
+    links: list[Link] | None = None
+    language: str | None = None
+    evaluation_time: set[str] | None = None
+    requirements: str | list[str] | None = None
+
+
+class ProblemLike(Thing):
+    name: str
+    long_name: str | None = None
+    description: str | None = None
+    tags: set[str] | None = None
+    references: set[Reference] | None = None
+    implementations: set[str] | None = None
+    objectives: set[int] | None = None
+    variables: set[Variable] | None = None
+    constraints: set[Constraint] | None = None
+    dynamic_type: set[str] | None = None
+    noise_type: set[str] | None = None
+    allows_partial_evaluation: YesNoSome | None = None
+    can_evaluate_objectives_independently: YesNoSome | None = None
+    modality: set[str] | None = None
+    fidelity_levels: set[int] | None = None
+    evaluation_time: set[str] | None = None
+    code_examples: set[str] | None = None
+    source: set[str] | None = None
+
+    def __hash__(self):
+        return hash((self.type, self.name))
+
+
+class Problem(ProblemLike):
+    type: OPLType = OPLType.problem
+    instances: ValueRange | list[str] | None = None
+
+
+class Suite(ProblemLike):
+    type: OPLType = OPLType.suite
+    problems: set[str] | None = None
+
+
+class Generator(ProblemLike):
+    type: OPLType = OPLType.generator
+
+
+class Library(RootModel):
+    root: dict[str, Problem | Generator | Suite | Implementation] = {}
+
+    def _check_id_references(self, ids, type: OPLType) -> None:
+        for id in ids:
+            if id in self.root:
+                if self.root[id].type != type:
+                    raise ValueError(
+                        f"ID {id} is a {self.root[id].name}, expected a {type.name}"
+                    )
+            else:
+                raise ValueError(f"Missing {type.name} with id '{id}'")
+
+    def _percolate_set(self, thing: Any, children: set | None, property: str):
+        """Propagate some `property` from child objects to the parent by calculating the union of all the child property sets.
+
+        This is useful to propagate properties like `variables`, `constraints`, etc. from problems up to the suite.
+        """
+        if children is None:
+            return
+
+        if getattr(thing, property, None) is None:
+            setattr(thing, property, set())
+        thing_set = getattr(thing, property)
+
+        for child_id in children:
+            child = self.root[child_id]
+            child_set = getattr(child, property, None)
+            if child_set is not None:
+                thing_set.update(child_set)
+
+    @model_validator(mode="after")
+    def _validate(self) -> Self:
+        # First check and fixup all problems
+        for id, thing in self.root.items():
+            if isinstance(thing, Problem) and thing.implementations:
+                self._percolate_set(thing, thing.implementations, "evaluation_time")
+
+        # Then check and fixup all suites because changes from the problems need to propagate to the suites
+        for id, thing in self.root.items():
+            if isinstance(thing, Suite) and thing.problems:
+                for problem_id in thing.problems:
+                    if problem_id not in self.root:
+                        raise ValueError(
+                            f"Suite {id} references problem with undefined id '{problem_id}'."
+                        )
+                    if self.root[problem_id].type != OPLType.problem:
+                        raise ValueError(
+                            f"Suite {id} references problem with id '{problem_id}' but id is a {self.root[problem_id].type.name}."
+                        )
+
+                self._percolate_set(thing, thing.problems, "fidelity_levels")
+                self._percolate_set(thing, thing.problems, "variables")
+                self._percolate_set(thing, thing.problems, "constraints")
+                self._percolate_set(thing, thing.problems, "evaluation_time")
+
+        return self
+
+
+__all__ = [
+    "Constraint",
+    "Generator",
+    "Implementation",
+    "Library",
+    "Link",
+    "Problem",
+    "Reference",
+    "Suite",
+    "Variable",
+    "YesNoSome",
+]
diff --git a/src/opltools/utils.py b/src/opltools/utils.py
new file mode 100644
index 0000000..a05a9b7
--- /dev/null
+++ b/src/opltools/utils.py
@@ -0,0 +1,63 @@
+from typing_extensions import Self
+from pydantic import BaseModel, model_validator
+
+
+class ValueRange(BaseModel):
+    min: int | None
+    max: int | None = None
+
+    @model_validator(mode="after")
+    def _check(self) -> Self:
+        if self.min is None and self.max is None:
+            raise ValueError("Variable range should have at least a min or max value.")
+        return self
+
+    def __hash__(self):
+        return hash((self.min, self.max))
+
+
+def _none_min(a, b):
+    if a and b:
+        return min(a, b)
+    elif a:
+        return a
+    else:
+        return b
+
+
+def _none_max(a, b):
+    if a and b:
+        return max(a, b)
+    elif a:
+        return a
+    else:
+        return b
+
+
+def union_range(
+    a: int | set[int] | ValueRange, b: int | set[int] | ValueRange
+) -> int | set[int] | ValueRange:
+    if isinstance(a, int):
+        a = {a}
+    if isinstance(b, int):
+        b = {b}
+
+    if isinstance(a, set) and isinstance(b, set):
+        res = a.union(b)
+        return res.pop() if len(res) == 1 else res
+    elif isinstance(a, ValueRange) and isinstance(b, ValueRange):
+        return ValueRange(min=_none_min(a.min, b.min), max=_none_max(a.max, b.max))
+
+    if isinstance(a, set):
+        a, b = b, a
+    if isinstance(a, ValueRange) and isinstance(b, set):
+        res = ValueRange(min=a.min, max=a.max)
+        if res.min:
+            for v in b:
+                res.min = min(v, res.min)
+        if res.max:
+            for v in b:
+                res.max = max(v, res.max)  #
+        return res
+
+    raise Exception("BAM")
diff --git a/src/opltools/yesnosome.py b/src/opltools/yesnosome.py
new file mode 100644
index 0000000..e10b24a
--- /dev/null
+++ b/src/opltools/yesnosome.py
@@ -0,0 +1,28 @@
+from enum import Enum
+
+
+class YesNoSome(Enum):
+    yes = "yes"
+    no = "no"
+    some = "some"
+    unknown = "?"
+
+
+def union(
+    a: YesNoSome | set[YesNoSome], b: YesNoSome | set[YesNoSome]
+) -> YesNoSome | set[YesNoSome]:
+    result = set()
+    if isinstance(a, YesNoSome):
+        result.add(a)
+    else:
+        result.update(a)
+
+    if isinstance(b, YesNoSome):
+        result.add(b)
+    else:
+        result.update(b)
+
+    if len(result) == 1:
+        return result.pop()
+    else:
+        return result
diff --git a/tests/__init__.py b/tests/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/test_constraints.py b/tests/test_constraints.py
new file mode 100644
index 0000000..782677e
--- /dev/null
+++ b/tests/test_constraints.py
@@ -0,0 +1,17 @@
+from opltools.schema import Constraint, YesNoSome
+
+
+class TestConstraint:
+    def test_default(self):
+        c = Constraint(type="box")
+        assert c.hard is None
+        assert c.equality is None
+        assert c.number is None
+
+    def test_hard(self):
+        c = Constraint(type="box", hard="yes")
+        assert c.hard == YesNoSome.yes
+
+    def test_number(self):
+        c = Constraint(type="linear", number=5)
+        assert c.number == 5
diff --git a/tests/test_generator.py b/tests/test_generator.py
new file mode 100644
index 0000000..9d32ea0
--- /dev/null
+++ b/tests/test_generator.py
@@ -0,0 +1,7 @@
+from opltools.schema import Generator, OPLType
+
+
+class TestGenerator:
+    def test_defaults(self):
+        g = Generator(name="G1")
+        assert g.type is OPLType.generator
diff --git a/tests/test_implementation.py b/tests/test_implementation.py
new file mode 100644
index 0000000..63a03e2
--- /dev/null
+++ b/tests/test_implementation.py
@@ -0,0 +1,31 @@
+from opltools.schema import Implementation, Link, OPLType
+
+
+class TestImplementation:
+    def test_defaults(self):
+        impl = Implementation(name="impl1", description="An implementation")
+        assert impl.type is OPLType.implementation
+        assert impl.name == "impl1"
+        assert impl.description == "An implementation"
+        assert impl.links is None
+        assert impl.language is None
+        assert impl.requirements is None
+
+    def test_full(self):
+        impl = Implementation(
+            name="impl1",
+            description="desc",
+            links=[Link(url="https://example.org")],
+            language="python",
+            evaluation_time=["fast"],
+            requirements=["numpy", "scipy"],
+        )
+        assert impl.language == "python"
+        assert impl.requirements == ["numpy", "scipy"]
+        assert len(impl.links) == 1
+
+    def test_requirements_as_string(self):
+        impl = Implementation(
+            name="impl1", description="d", requirements="numpy"
+        )
+        assert impl.requirements == "numpy"
diff --git a/tests/test_library.py b/tests/test_library.py
new file mode 100644
index 0000000..542bc7b
--- /dev/null
+++ b/tests/test_library.py
@@ -0,0 +1,98 @@
+import pytest
+from pydantic import ValidationError
+
+from opltools.schema import (
+    Generator,
+    Implementation,
+    Library,
+    Problem,
+    Suite,
+)
+
+
+class TestLibrary:
+    def test_empty(self):
+        lib = Library(root={})
+        assert lib.root == {}
+
+    def test_single_problem(self):
+        lib = Library(root={"p1": Problem(name="P1")})
+        assert "p1" in lib.root
+        assert isinstance(lib.root["p1"], Problem)
+
+    def test_multiple_things(self):
+        lib = Library(root={
+            "p1": Problem(name="P1"),
+            "p2": Problem(name="P2"),
+            "g1": Generator(name="G1"),
+            "s1": Suite(name="S1", problems={"p1", "p2"}),
+            "impl1": Implementation(name="impl1", description="d"),
+        })
+        assert len(lib.root) == 5
+        assert isinstance(lib.root["p1"], Problem)
+        assert isinstance(lib.root["g1"], Generator)
+        assert isinstance(lib.root["s1"], Suite)
+        assert isinstance(lib.root["impl1"], Implementation)
+
+    def test_suite_references_missing_problem(self):
+        with pytest.raises(ValidationError, match="undefined id"):
+            Library(root={
+                "s1": Suite(name="S1", problems={"does-not-exist"}),
+            })
+
+    def test_suite_references_non_problem(self):
+        with pytest.raises(ValidationError, match="but id is a"):
+            Library(root={
+                "g1": Generator(name="G1"),
+                "s1": Suite(name="S1", problems={"g1"}),
+            })
+
+    def test_suite_with_no_problems_is_valid(self):
+        lib = Library(root={"s1": Suite(name="S1")})
+        assert lib.root["s1"].problems is None
+
+    def test_fixup_fidelity_populates_from_problems(self):
+        lib = Library(root={
+            "p1": Problem(name="P1", fidelity_levels={1, 2}),
+            "p2": Problem(name="P2", fidelity_levels={2, 3}),
+            "s1": Suite(name="S1", problems={"p1", "p2"}),
+        })
+        assert lib.root["s1"].fidelity_levels == {1, 2, 3}
+
+    def test_fixup_fidelity_extends_existing(self):
+        lib = Library(root={
+            "p1": Problem(name="P1", fidelity_levels={5}),
+            "s1": Suite(name="S1", problems={"p1"}, fidelity_levels={10}),
+        })
+        assert lib.root["s1"].fidelity_levels == {5, 10}
+
+    def test_fixup_fidelity_with_problems_without_levels(self):
+        lib = Library(root={
+            "p1": Problem(name="P1"),
+            "p2": Problem(name="P2", fidelity_levels={7}),
+            "s1": Suite(name="S1", problems={"p1", "p2"}),
+        })
+        assert lib.root["s1"].fidelity_levels == {7}
+
+    def test_fixup_fidelity_all_problems_without_levels(self):
+        lib = Library(root={
+            "p1": Problem(name="P1"),
+            "s1": Suite(name="S1", problems={"p1"}),
+        })
+        assert lib.root["s1"].fidelity_levels == set()
+
+    def test_fixup_evaluation_time_percolates_from_implementation_to_suite(self):
+        lib = Library(root={
+            "impl1": Implementation(
+                name="impl1", description="d", evaluation_time={"fast"}
+            ),
+            "impl2": Implementation(
+                name="impl2", description="d", evaluation_time={"8 minutes"}
+            ),
+            "p1": Problem(name="P1", implementations={"impl1"}),
+            "p2": Problem(name="P2", implementations={"impl2"}),
+            "s1": Suite(name="S1", problems={"p1", "p2"}),
+        })
+        assert lib.root["p1"].evaluation_time == {"fast"}
+        assert lib.root["p2"].evaluation_time == {"8 minutes"}
+        assert lib.root["s1"].evaluation_time == {"fast", "8 minutes"}
diff --git a/tests/test_link.py b/tests/test_link.py
new file mode 100644
index 0000000..6f8a31c
--- /dev/null
+++ b/tests/test_link.py
@@ -0,0 +1,19 @@
+import pytest
+from pydantic import ValidationError
+
+from opltools.schema import Link
+
+
+class TestLink:
+    def test_minimal(self):
+        link = Link(url="https://example.org")
+        assert link.url == "https://example.org"
+        assert link.type is None
+
+    def test_with_type(self):
+        link = Link(type="homepage", url="https://example.org")
+        assert link.type == "homepage"
+
+    def test_url_required(self):
+        with pytest.raises(ValidationError):
+            Link()
diff --git a/tests/test_objectives.py b/tests/test_objectives.py
new file mode 100644
index 0000000..944404d
--- /dev/null
+++ b/tests/test_objectives.py
@@ -0,0 +1,31 @@
+from opltools.schema import Objectives
+from opltools.utils import ValueRange
+
+
+class TestObjectives:
+    def test_default(self):
+        obj = Objectives()
+        assert obj.root == 0
+
+    def test_int(self):
+        assert Objectives(root=3).root == 3
+
+    def test_set(self):
+        assert Objectives(root={1, 2, 3}).root == {1, 2, 3}
+
+    def test_range(self):
+        obj = Objectives(root=ValueRange(min=1, max=5))
+        assert obj.root.min == 1
+        assert obj.root.max == 5
+
+    def test_union_ints(self):
+        a = Objectives(root=1)
+        b = Objectives(root=2)
+        a.union(b)
+        assert a.root == {1, 2}
+
+    def test_union_same_int(self):
+        a = Objectives(root=1)
+        b = Objectives(root=1)
+        a.union(b)
+        assert a.root == 1
diff --git a/tests/test_opltype.py b/tests/test_opltype.py
new file mode 100644
index 0000000..db42057
--- /dev/null
+++ b/tests/test_opltype.py
@@ -0,0 +1,15 @@
+import pytest
+
+from opltools.schema import OPLType
+
+
+class TestOPLType:
+    def test_from_string(self):
+        assert OPLType("problem") is OPLType.problem
+        assert OPLType("implementation") is OPLType.implementation
+        assert OPLType("suite") is OPLType.suite
+        assert OPLType("generator") is OPLType.generator
+
+    def test_bad_string(self):
+        with pytest.raises(ValueError):
+            OPLType("foo")
diff --git a/tests/test_problem.py b/tests/test_problem.py
new file mode 100644
index 0000000..f3a9498
--- /dev/null
+++ b/tests/test_problem.py
@@ -0,0 +1,28 @@
+from opltools.schema import OPLType, Problem
+from opltools.utils import ValueRange
+
+
+class TestProblem:
+    def test_defaults(self):
+        p = Problem(name="P1")
+        assert p.type is OPLType.problem
+        assert p.name == "P1"
+        assert p.instances is None
+
+    def test_with_tags_and_objectives(self):
+        p = Problem(
+            name="P1",
+            tags={"convex", "smooth"},
+            objectives={1, 2},
+        )
+        assert p.tags == {"convex", "smooth"}
+        assert p.objectives == {1, 2}
+
+    def test_instances_list(self):
+        p = Problem(name="P1", instances=["i1", "i2"])
+        assert p.instances == ["i1", "i2"]
+
+    def test_instances_range(self):
+        p = Problem(name="P1", instances=ValueRange(min=1, max=10))
+        assert p.instances.min == 1
+        assert p.instances.max == 10
diff --git a/tests/test_problemlike.py b/tests/test_problemlike.py
new file mode 100644
index 0000000..9e6a4a6
--- /dev/null
+++ b/tests/test_problemlike.py
@@ -0,0 +1,26 @@
+import pytest
+from pydantic import ValidationError
+
+from opltools.schema import Problem, ProblemLike, YesNoSome
+
+
+class TestProblemLike:
+    def test_shared_fields(self):
+        p = Problem(
+            name="P1",
+            long_name="Problem 1",
+            description="desc",
+            tags={"convex", "smooth"},
+            allows_partial_evaluation=YesNoSome.yes,
+            can_evaluate_objectives_independently=YesNoSome.no,
+            modality={"unimodal"},
+            fidelity_levels={1, 2, 3},
+        )
+        assert p.long_name == "Problem 1"
+        assert p.tags == {"convex", "smooth"}
+        assert p.allows_partial_evaluation is YesNoSome.yes
+        assert p.fidelity_levels == {1, 2, 3}
+
+    def test_problemlike_not_directly_useful_without_type(self):
+        with pytest.raises(ValidationError):
+            ProblemLike(name="X")
diff --git a/tests/test_reference.py b/tests/test_reference.py
new file mode 100644
index 0000000..0d388a6
--- /dev/null
+++ b/tests/test_reference.py
@@ -0,0 +1,28 @@
+import pytest
+from pydantic import ValidationError
+
+from opltools.schema import Link, Reference
+
+
+class TestReference:
+    def test_only_author(self):
+        ref = Reference(title="A paper")
+        assert ref.title == "A paper"
+        assert ref.authors is None
+        assert ref.link is None
+
+    def test_only_link(self):
+        ref = Reference(link=Link(url="https://example.org"))
+        assert ref.link.url == "https://example.org"
+
+    def test_full(self):
+        ref = Reference(
+            title="A paper",
+            authors=["Alice"],
+            link=Link(url="https://example.org"),
+        )
+        assert ref.link.url == "https://example.org"
+
+    def test_requires_title_or_link(self):
+        with pytest.raises(ValidationError):
+            Reference(authors=["A paper"])
diff --git a/tests/test_suite.py b/tests/test_suite.py
new file mode 100644
index 0000000..ab686db
--- /dev/null
+++ b/tests/test_suite.py
@@ -0,0 +1,12 @@
+from opltools.schema import OPLType, Suite
+
+
+class TestSuite:
+    def test_defaults(self):
+        s = Suite(name="S1")
+        assert s.type is OPLType.suite
+        assert s.problems is None
+
+    def test_with_problems(self):
+        s = Suite(name="S1", problems={"p1", "p2"})
+        assert s.problems == {"p1", "p2"}
diff --git a/tests/test_thing.py b/tests/test_thing.py
new file mode 100644
index 0000000..e92f795
--- /dev/null
+++ b/tests/test_thing.py
@@ -0,0 +1,16 @@
+import pytest
+from pydantic import ValidationError
+
+from opltools.schema import OPLType, Thing
+
+
+class TestThing:
+    def test_type_required(self):
+        with pytest.raises(ValidationError):
+            Thing()
+
+    def test_allows_extra_fields(self):
+        thing = Thing(type=OPLType.problem, something_extra="value", count=3)
+        assert thing.type is OPLType.problem
+        assert thing.something_extra == "value"
+        assert thing.count == 3
diff --git a/tests/test_union_range.py b/tests/test_union_range.py
new file mode 100644
index 0000000..aff681c
--- /dev/null
+++ b/tests/test_union_range.py
@@ -0,0 +1,61 @@
+from opltools.utils import ValueRange, union_range
+
+
+class TestUnionRange:
+    def test_int_and_same_int(self):
+        assert union_range(3, 3) == 3
+
+    def test_int_and_different_int(self):
+        assert union_range(1, 2) == {1, 2}
+
+    def test_int_and_set(self):
+        assert union_range(1, {2, 3}) == {1, 2, 3}
+
+    def test_set_and_set(self):
+        assert union_range({1, 2}, {2, 3}) == {1, 2, 3}
+
+    def test_set_collapses_to_int(self):
+        assert union_range({5}, {5}) == 5
+
+    def test_range_and_range(self):
+        a = ValueRange(min=1, max=5)
+        b = ValueRange(min=3, max=10)
+        result = union_range(a, b)
+        assert isinstance(result, ValueRange)
+        assert result.min == 1
+        assert result.max == 10
+
+    def test_range_and_range_with_none_bounds(self):
+        a = ValueRange(min=1, max=None)
+        b = ValueRange(min=None, max=10)
+        result = union_range(a, b)
+        assert result.min == 1
+        assert result.max == 10
+
+    def test_range_and_set_extends_max(self):
+        r = ValueRange(min=1, max=5)
+        result = union_range(r, {10})
+        assert isinstance(result, ValueRange)
+        assert result.min == 1
+        assert result.max == 10
+
+    def test_range_and_set_extends_min(self):
+        r = ValueRange(min=5, max=10)
+        result = union_range(r, {1})
+        assert isinstance(result, ValueRange)
+        assert result.min == 1
+        assert result.max == 10
+
+    def test_set_and_range_swapped(self):
+        r = ValueRange(min=5, max=10)
+        result = union_range({1}, r)
+        assert isinstance(result, ValueRange)
+        assert result.min == 1
+        assert result.max == 10
+
+    def test_int_and_range(self):
+        r = ValueRange(min=5, max=10)
+        result = union_range(1, r)
+        assert isinstance(result, ValueRange)
+        assert result.min == 1
+        assert result.max == 10
diff --git a/tests/test_usage.py b/tests/test_usage.py
new file mode 100644
index 0000000..2073f93
--- /dev/null
+++ b/tests/test_usage.py
@@ -0,0 +1,15 @@
+import pytest
+from pydantic import ValidationError
+
+from opltools.schema import Usage
+
+
+class TestUsage:
+    def test_basic(self):
+        u = Usage(language="python", code="print('hi')")
+        assert u.language == "python"
+        assert u.code == "print('hi')"
+
+    def test_requires_fields(self):
+        with pytest.raises(ValidationError):
+            Usage(language="python")
diff --git a/tests/test_valuerange.py b/tests/test_valuerange.py
new file mode 100644
index 0000000..19729b6
--- /dev/null
+++ b/tests/test_valuerange.py
@@ -0,0 +1,25 @@
+import pytest
+from pydantic import ValidationError
+
+from opltools.utils import ValueRange
+
+
+class TestValueRange:
+    def test_valid(self):
+        r = ValueRange(min=1, max=10)
+        assert r.min == 1
+        assert r.max == 10
+
+    def test_min_only(self):
+        r = ValueRange(min=1, max=None)
+        assert r.min == 1
+        assert r.max is None
+
+    def test_max_only(self):
+        r = ValueRange(min=None, max=10)
+        assert r.min is None
+        assert r.max == 10
+
+    def test_both_none_rejected(self):
+        with pytest.raises(ValidationError, match="at least a min or max"):
+            ValueRange(min=None, max=None)
diff --git a/tests/test_variables.py b/tests/test_variables.py
new file mode 100644
index 0000000..1345655
--- /dev/null
+++ b/tests/test_variables.py
@@ -0,0 +1,23 @@
+from opltools.schema import Variable, VariableType
+from opltools.utils import ValueRange
+
+
+class TestVariable:
+    def test_defaults(self):
+        v = Variable()
+        assert v.type is VariableType.unknown
+        assert v.dim == 0
+
+    def test_explicit_values(self):
+        v = Variable(type="continuous", dim=5)
+        assert v.type is VariableType.continuous
+        assert v.dim == 5
+
+    def test_range_dim(self):
+        v = Variable(type="integer", dim=ValueRange(min=1, max=10))
+        assert v.dim.min == 1
+        assert v.dim.max == 10
+
+    def test_set_dim(self):
+        v = Variable(type="binary", dim={2, 4})
+        assert v.dim == {2, 4}
diff --git a/tests/test_yesnosome.py b/tests/test_yesnosome.py
new file mode 100644
index 0000000..7667cd4
--- /dev/null
+++ b/tests/test_yesnosome.py
@@ -0,0 +1,39 @@
+import pytest
+
+from opltools.schema import YesNoSome
+from opltools.yesnosome import union
+
+
+class TestYesNoSome:
+    def test_from_string(self):
+        assert YesNoSome("yes") == YesNoSome.yes
+        assert YesNoSome("no") == YesNoSome.no
+        assert YesNoSome("some") == YesNoSome.some
+        assert YesNoSome("?") == YesNoSome.unknown
+
+    def test_bad_string(self):
+        with pytest.raises(ValueError):
+            YesNoSome("foo")
+
+
+class TestUnion:
+    def test_same_single(self):
+        assert union(YesNoSome.yes, YesNoSome.yes) == YesNoSome.yes
+
+    def test_different_singles(self):
+        assert union(YesNoSome.yes, YesNoSome.no) == {YesNoSome.yes, YesNoSome.no}
+
+    def test_single_and_set(self):
+        result = union(YesNoSome.yes, {YesNoSome.no, YesNoSome.some})
+        assert result == {YesNoSome.yes, YesNoSome.no, YesNoSome.some}
+
+    def test_set_and_single(self):
+        result = union({YesNoSome.some}, YesNoSome.yes)
+        assert result == {YesNoSome.yes, YesNoSome.some}
+
+    def test_set_and_set(self):
+        result = union({YesNoSome.yes, YesNoSome.no}, {YesNoSome.no, YesNoSome.some})
+        assert result == {YesNoSome.yes, YesNoSome.no, YesNoSome.some}
+
+    def test_set_collapses_to_single(self):
+        assert union({YesNoSome.yes}, {YesNoSome.yes}) == YesNoSome.yes
diff --git a/uv.lock b/uv.lock
new file mode 100644
index 0000000..9850ab7
--- /dev/null
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