data-science-engineering-foundation

State, resume, reconstruction, job-lifecycle, transition, and flow-state mechanics for the Data Science and Engineering Coach. Loaded by the coach; not a user entry point.

Data Science and Engineering Foundation

Goal

Keep Data Science and Engineering Coach orchestration consistent across job changes and sessions without duplicating job-specific guidance. The coach loads this index at initialization and resume, then reads the reference for the current coaching moment.

Reference index

Reference	When to read
job-registry.md	Before offering or selecting a job, routing to a skill or specialist, or naming a durable output
lifecycle-classes.md	When starting, pausing, resuming, completing, or re-invoking a job
transition-protocol.md	When a topic shift, explicit request, or completion suggests moving between jobs
session-state.md	Before initialization, validation, mutation, resume, recovery, or reconstruction of coaching state
flow-state.md	Before interrupting work, crossing a gate, writing a durable artifact, or offering post-job choices

Success criteria

Each orchestration rule has one owner in this package.
State and lifecycle mechanics remain independent of job-specific methods.
The coach reads the applicable reference before acting on its contract.

Constraints

Keep catalog guidance in data-catalog, the durable data-catalog workflow for entities, declared relationships, lineage, and ERD-ready model semantics.
Keep feasibility guidance in feasibility, the evidence-led data and ML feasibility-study workflow with lifecycle and interchange traceability.
Keep pipeline and testing guidance in dataops, the DataOps reference for tier behavior, pipeline invariants, validation placement, tests, drift, and operational signals.
Keep general experiment guidance in experiment-design, the reusable workflow for candidate selection, hypotheses, vetting, minimum scope, and result evaluation.
Keep ML-specific experiment guidance in ml-experimentation, the reference for ML environments, reproducibility, tracking, evaluation, abstractions, and production readiness.
Keep notebook and dashboard guidance in analysis-authoring, the reference for EDA notebook and analytical dashboard composition, visualization selection, and dashboard validation.
Keep AI-system evaluation guidance in evaluation-design, the reference for evaluation dataset design, difficulty balance, metric selection, and tooling fit.
Treat this package as internal foundation knowledge, not a user-selectable workflow.
Preserve the skill authority boundaries and cross-cutting concerns defined in the job registry.

Stop rules

Stop before a state mutation when the session-state protocol has not been loaded or project identity is uncertain.
Stop before a job switch when the user has not confirmed the transition.
Stop and report the missing owner when requested behavior belongs to neither this foundation nor a registered job capability.

Attribution

This package is repository-original orchestration guidance licensed under CC BY 4.0. It does not reproduce or summarize an external standard.