wicked-garden-domain-modeler

Modernize Translator

This skill is designed to run as an isolated worker; when your harness cannot fork, run it inline and keep its output separate from the caller's.

You turn a flat set of extracted rules into a cluster-keyed domain model and invoke core's domain-graph build to produce the requirements graph. A domain is derived from an estate Louvain community, not hand-partitioned.

Contract you emit against

Same vendored [email protected] schema as the extractor. Your domains{} grouping — each domain groups the requirements whose components fall in one estate community, carries an advisory cluster_id (the Louvain index), and declares its entities{} — is advisory provenance. The authoritative requirements graph is built by core from the annotated store (core derives domains from estate's communities). You invoke core, you don't reimplement it.

The loop

1. Read clusters from estate — the full-membership feed clusters --json --summary → [{id, size, members:[symbol_id], …}], via estate_client(db).read_clusters() (CLI) or _mocks.EstateClient (hermetic). On the real path this is informational (core derives the authoritative domains when it builds the graph); the id is a volatile positional index, so key durable grouping on a hash of the sorted member set, not the raw id (record the raw id only as advisory cluster_id).
2. Assign each requirement to a domain by the community its legacy_components[] SymbolIds belong to (advisory grouping / provenance for the antagonist). A requirement whose components span communities goes to the dominant one; note the split.
3. Invoke core's domain-graph build. core_client().domain_graph(db, out) shells wicked-core domain-graph --db <db> --out requirements_graph.json, which reads the annotated store, recomputes front-half coverage, and builds requirements_graph.json (a capability plan, not a code skeleton). It fails closed (writes nothing, non-zero exit) if coverage < 1.0 — every behavior-bearing node must already be annotated (the extractor's job). There is no doc handed in and no --overlay: the store is the input. When core_client() is None (no peer), fall back to the hermetic lane — emit_domain_model.py assembles the doc and _mocks.BrainClient stands in.
4. Validate core's output. Cross-check the built requirements_graph.json with scripts/domain/validate_domain_model.py (schema + hard invariants) before returning.