docs: add domain boundary READMEs for governance anchors
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calibration/README.md
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calibration/README.md
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# Calibration Package
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`calibration/` is the deterministic operator-parameter replay and tuning
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package. It explores bounded `CalibrationParams` candidates against eval cases
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and emits before/after metrics for review.
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It is not the ADR-0175 reliability ledger and it does not grant serving
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licenses. Serving discipline is owned by `core.reliability_gate`; Workbench reads
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that evidence through `workbench/calibration.py` without re-running lanes or
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mutating license state.
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This boundary is intentional:
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- `calibration/params.py`, `calibration/replay.py`, `calibration/tune.py`, and
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`calibration/report.py` support deterministic parameter audits.
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- `workbench/calibration.py` projects committed practice and serving artifacts
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into a read-only UI/API surface.
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contemplation/README.md
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contemplation/README.md
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# Contemplation Artifacts
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This directory is an artifact namespace for committed contemplation process
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reports, especially the `runs/` evidence consumed by teaching queue and
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Workbench readers.
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It is intentionally not a Python package:
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- no `contemplation/__init__.py`
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- no Python source files under this tree
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- executable contemplation code lives under `core/contemplation/`
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- always-on runtime life writes local reports under
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`<engine_state>/contemplation_runs/`
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Keeping this split explicit prevents `import contemplation` ambiguity while
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preserving the deterministic JSON evidence shape expected by queue and
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Workbench surfaces.
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core/demos/README.md
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core/demos/README.md
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# Demo Composition Layer
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`core/demos/` contains the typed composition surface for demos:
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contracts, adapters, showcase rendering, and expert-demo packaging.
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It does not own standalone scenario fixtures. Those live under top-level
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`demos/`, where each demo package can pin its inputs, expected artifacts, and
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honesty ledger.
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Boundary:
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- `demos/` proves a narrow claim inside a deterministic local envelope.
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- `core/demos/` adapts proven demos into shared presentation and Workbench
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surfaces.
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core_ingest/README.md
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core_ingest/README.md
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# Core Ingest
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`core_ingest/` converts external source material into typed candidate pressure:
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content-addressed packets with provenance, modality, determinism class, review
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level, and semantic keys.
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Its durable path runs the three-gate `IngestCompiler` and can export
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`LearningArtifact` objects. Its read-only CLI surface (`core ingest compile`) is
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for inspection and does not write vault entries, mutate packs, ratify learning,
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or call `ingest/gate.py`.
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Boundary:
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- `core_ingest` prepares and validates candidate pressure.
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- `ingest/gate.py` injects runtime field state into the versor manifold.
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- durable mutation still belongs to the reviewed teaching path.
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demos/README.md
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demos/README.md
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# Deterministic Demo Packages
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`demos/` contains standalone, claim-scoped demonstration packages. Each demo
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has its own fixtures, expected artifacts, local authority code, and runner.
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These packages are intentionally importable because tests and Workbench demo
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routes execute them as deterministic envelopes. They are not generic runtime
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adapters and they must not perform hidden side effects.
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Use this directory for bounded proof demos such as proposer authority,
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proof-carrying promotion, epistemic truth-state refusal, or domain-specific
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decision substrates.
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Use `core/demos/` for composition contracts, showcase adapters, and runtime
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presentation of already-proven demos.
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ingest/README.md
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ingest/README.md
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# Runtime Ingest Gate
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`ingest/` owns the runtime injection boundary: raw token/state material enters
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the versor manifold through `ingest/gate.py`.
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This is an allowed normalization boundary. `inject()` calls
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`algebra.versor.normalize_to_versor()` once at construction time and returns a
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`FieldState` satisfying the field invariant.
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It is not the durable learning compiler. Candidate learning material should be
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prepared by `core_ingest` and reviewed through the teaching/governance path
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before it becomes durable standing.
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language_packs/README.md
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language_packs/README.md
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# Language Packs
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`language_packs/` owns reviewed language-pack loading and compilation. It turns
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pack manifests, lexicon rows, morphology, grammar attractors, and alignment
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metadata into runtime vocab/manifold structures.
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This compiler is distinct from `core_ingest.compiler`:
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- `language_packs.compiler` consumes reviewed pack data and builds linguistic
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runtime structures.
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- `core_ingest.compiler` consumes external candidate pressure and produces
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validation reports plus provisional learning artifacts.
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The shared word "compiler" means "deterministic lowering across a boundary";
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the source material, trust boundary, and output structures are different.
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workbench/README.md
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workbench/README.md
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# CORE Workbench Backend
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`workbench/` is the local operator/auditor API package for CORE. It exposes
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read models over committed artifacts, runtime traces, evidence bundles, demo
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envelopes, calibration ledgers, and narrow allowlisted actions.
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It is distinct from:
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- `workbench-ui/` — the React/Vite frontend.
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- `workbench_data/` — ignored local read-model artifacts such as turn journals.
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- `docs/workbench/` — plans, contracts, guides, and design documentation.
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Backend modules should preserve the Workbench trust boundary:
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- read-only by default;
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- no hidden model calls or background execution;
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- execution only through explicit allowlisted endpoints;
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- artifact projections must include source paths/digests when available.
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`apple_uma_report.py` belongs here because it projects a persisted benchmark
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report into a stable UI/API read model. It does not run benchmarks, import MLX,
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mutate reports, or authorize serving.
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