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easy-cheese-schemas

The machine-readable artifact contracts of easy-cheese, published as an installable package: run manifests, decompositions, curd blocks, PR plans, and the readiness gate, as attrs types with cattrs structuring and explicit schema-version tolerance.

pip install easy-cheese-schemas

Requires Python 3.11 or newer. cattrs floors at 3.10; 3.11+ skips the exceptiongroup dependency, and 3.10 reaches end of life in October 2026.

Package boundary

easy_cheese_schemas defines shared contracts, not workflow execution. It owns types, invariants, pure normalization, validation, canonical serialization, and schema generation. Pure planner materialization stays here because it transforms supplied values without dispatch or artifact access.

Runtime consumers depend on schemas; schemas must not depend on runtime consumers.

Responsibility Owner
Planner, Cook, Cure, and callback execution easy_cheese.shared.workflow
Artifact resolution, verification, and local retention easy_cheese.shared.artifacts
Artifact publication and handoff acceptance easy_cheese.shared.publication
Repository benchmarks and build compilers scripts/

Import runtime functions from their owning module.

The schema package does not provide compatibility re-exports. Runtime callback records and exceptions stay with their runtime module. Persisted semantic contracts stay in schemas.

Mold-to-Cook boundary values

Mold hands bound work to Cook through direct references, not a published schema. A ready finalization carries request_id, spec_ref, planner_result_ref, plan_ref, and exact MoldCookCoverage. The host validates every reference before any writer runs. CookSetupAuthorization is limited to its named prerequisite curd, authorized paths, and authorized commands; setup evidence does not clear unrelated holds. Partial coverage preserves the acknowledged unresolved work until it is completed or explicitly disposed.

What this is, and what it is not

It is the artifact vocabulary: the types an external producer or consumer needs to write or read an easy-cheese document without reimplementing its field rules.

The schema package is the canonical enforcement path for the structural and collection invariants listed above. load and validate_contract structure and validate versioned values before a producer or consumer can treat them as contracts. Runtime modules still own checks that require artifact resolution, execution context, or phase state; those remain listed below. A successful Loaded is necessary but does not by itself grant execution authority.

These are versioned canonical models, not derivatives of older hand-rolled validators. The package has no compatibility re-exports; callers use explicit runtime boundary validators when artifact or phase evidence is required.

Also not published: easy-cheese's corpus and layout assumptions (paths.py) and the findings report grammar. Those are repo-internal and stay unversioned on purpose.

Runtime-owned checks

The types check field shape and the collection invariants below, while runtime validators retain checks that need resolved evidence or current phase state.

Enforced here: required fields and their types, enum membership, curd file-disjointness, wiring DAG acyclicity and unknown W<n> references, wave size and curd surface floors, and the PR-plan shape rules.

Not enforced here, and checked only by the runtime validators:

  • agent_resolution consistency — exactly one accepted attempt; the resolved agent matching that attempt; attempt and resolved power meeting the request's minimum_power; prompt-only permission enforcement implying degraded and a read-only request; an unknown resolved power implying degraded; a preferred-exact acceptance carrying a null fallback_reason (and a non-preferred one carrying a reason).
  • Phase-dependent requirements — phase of post_review_complete or pr_publish_complete requiring current_review / post_review.
  • Curd lifecycle — a curd with status: completed requiring review_context.

These checks intentionally remain with runtime modules because they require resolved evidence or current phase state; they are not a temporary migration gap.

Usage

load structures a raw mapping into one of the artifact types. It never raises: it returns a Loaded carrying the value (or None), the payload's provenance, and every problem it found, in the same where.key must be ... format easy-cheese's validators emit.

from easy_cheese_schemas import PrGroup, load

plan = {
    "schema_version": 1,
    "branch": "feat/publish",
    "title": "Publish the schemas package",
    "base": "main",
    "commits": ["9f2c1ab"],
}
strict = load(plan, PrGroup, strict=True)
print(strict.provenance, strict.problems)
print(strict.value)

# Written by a newer producer: unknown fields are ignored, the rest still parses.
newer = load(plan | {"schema_version": 2, "reviewers": ["ada"]}, PrGroup, strict=True)
print(newer.provenance, newer.value.branch)

# Lenient: gaps are reported, not raised, and the value is still usable.
lenient = load(plan | {"depends_on": None}, PrGroup, strict=False)
print(lenient.provenance, lenient.problems)
print(lenient.value)
Provenance.CURRENT ()
PrGroup(branch='feat/publish', title='Publish the schemas package', base='main', commits=['9f2c1ab'], body=None, depends_on=[])
Provenance.FUTURE feat/publish
Provenance.CURRENT ('PrGroup.body must be present; using default', 'PrGroup.depends_on must be a list, not NoneType')
PrGroup(branch='feat/publish', title='Publish the schemas package', base='main', commits=['9f2c1ab'], body=None, depends_on=[])

Problems accumulate; load reports every one it found in a single pass rather than stopping at the first, because the callers reporting them to a human need the whole list. problems is a tuple[str, ...] — Loaded is frozen, and a mutable list on a frozen carrier is an invitation to edit the evidence.

Values are not type-coerced. A str where a list[str] belongs is a problem, not eight one-character paths; "no" where a bool belongs is a problem, not True. Reading a document is how you find out whether to trust it, so this layer reports the mismatch rather than papering over it.

One case returns a value and problems: a schema_version stamp that is not an integer is recorded as a problem and the payload is treated as UNSTAMPED, because an untrustworthy stamp is not a reason to discard an otherwise readable document. Callers that gate on value is not None should check problems too.

The schema_version contract

SCHEMA_VERSION = 4   # what this package writes and fully understands
MIN_READABLE = 1     # oldest stamp still readable; widens as the schema evolves
STAMP_KEY = "schema_version"

The real coupling is the data boundary, not the code boundary. A vendored bundle is internally consistent by construction — it ships its own copy of these types — but persisted artifacts in the durable corpus outlive the upgrade that rewrote the reader, and external producers are the entire point of publishing. So every payload carries its vintage, and a reader can tell what it is holding before it acts on it.

classify_stamp maps the stamp to one of five outcomes:

Provenance Stamp condition Meaning
CURRENT stamp == SCHEMA_VERSION Written against this exact schema.
PRIOR MIN_READABLE <= stamp < SCHEMA_VERSION One or more versions behind, still readable — the N-1 tolerance.
UNSTAMPED key absent (or present but not an int, which is also reported as a problem) No stamp. Normal for a hand-authored document, foreign for a manifest.
STALE stamp < MIN_READABLE Older than this reader supports.
FUTURE stamp > SCHEMA_VERSION Written by a newer easy-cheese.

FUTURE is not a rejection. Recognized fields parse, unknown fields are ignored, and the caller gets provenance=FUTURE so it can decide whether to act, warn, or refuse. Provenance is orthogonal to validity: a FUTURE payload can still be structurally invalid, and a CURRENT one can still collect problems.

Two-tier strictness by artifact class

load does not decide strictness — strict is the caller's keyword argument. The tiers are a convention about which default each artifact class deserves:

  • Markdown documents (specs, findings, handoffs) are hand-authored and hand-edited. A missing stamp is normal, so they are read lenient: documented defaults are filled in, every gap is recorded in problems, and the caller still gets a usable value.
  • JSON/YAML manifests are machine-written. A missing stamp means the payload is foreign, so they are read strict: full cattrs validation, with the raised exception group flattened into problems and value=None on failure. An explicit --lax escape exists at the CLI boundary for the case where a human is knowingly hand-repairing a manifest.

Stability policy

The package is semver'd, and the version governs the artifact contracts, not just the Python API. SCHEMA_VERSION and the package version move independently: a schema bump is always a major bump, but not every major bump is a schema bump.

  • Patch — no contract change. Bug fixes, problem-message wording, documentation.
  • Minor — additive only. New optional fields, new types, new exports. Every artifact a previous minor could write is still read as CURRENT, and every artifact a previous minor could read still parses.
  • Major — a breaking contract change: a removed or renamed field, a narrowed type, a field made required, or a raised MIN_READABLE. Accompanied by a SCHEMA_VERSION bump, so previously-written artifacts become PRIOR or STALE rather than silently misparsing.

The additive-only discipline is what makes FUTURE provenance safe, and it is a hard rule, not a preference. Because unknown fields are ignored, an older reader handed a newer artifact will silently drop anything it does not recognize. That is correct behavior when new fields are additive and optional, and it is data loss when they are not — the older reader would produce a value that looks complete and is not. So within a SCHEMA_VERSION, new fields must be additive and optional. Anything else waits for the major bump.

Pre-1.0 caveat: while the version is 0.x, minor bumps may break. The policy above binds from 1.0.

Releasing (repo owner)

A pending publisher must exist on PyPI before the first publish. Publishing uses PyPI Trusted Publishing (OIDC), so no long-lived token is stored in the repository — but that means PyPI has to be told, in advance, which workflow in which repository is allowed to publish. Create the pending publisher on PyPI with the project name, the repository, and the publishing workflow's filename. This is a one-time manual step and it cannot be automated: without it, the first release run fails at upload.

After that, releases are automatic — a version bump to pyproject.toml landing on main triggers the publish.

License

MIT.

Metadata

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