Build Model

Command: build-model

Inputs

• use_case – name of metric or dashboard relying on the model.
• stack – modeling tool (dbt, LookML, Metrics Layer, SQL Runner, Python jobs).
• refresh – cadence (hourly, daily, weekly) or cron.
• dependencies – optional upstream tables or APIs.
• tests – optional list of validations to enforce.

GTM Agents Pattern & Plan Checklist

Mirrors GTM Agents orchestrator blueprint @puerto/plugins/orchestrator/README.md#112-325.

• Pattern selection: Modeling often runs pipeline (spec → blueprint → testing → deployment → docs). If testing + deployment prep can parallelize, log a diamond segment with merge gate.
• Plan schema: Save .claude/plans/plan-<timestamp>.json with objective, data lineage, task IDs, parallel groups, dependency matrix, error handling, and success metrics (freshness %, defect ceiling, SLA adherence).
• Tool hooks: Reference docs/gtm-essentials.md stack—Serena for repo diffs/dbt patches, Context7 for platform docs, Sequential Thinking for review cadences, Playwright for UI validations tied to modeled data.
• Guardrails: Default retry limit = 2 for failed tests/deployments; escalation path = Analytics Modeling Lead → Data Engineering Lead → RevOps.
• Review: Run docs/usage-guide.md#orchestration-best-practices-puerto-parity before execution to confirm agents, dependencies, deliverables.

Workflow

1. Spec Alignment – review event/tracking plan, KPI definitions, stakeholders.
2. Model Blueprint – outline staging, intermediate, mart layers, join keys, surrogate IDs.
3. Testing Strategy – define schema, freshness, unique, accepted value, and custom tests.
4. Deployment Plan – schedule jobs, resource configs, backfill strategy, rollback steps.
5. Documentation & Handoff – update dbt docs / catalog, change log, owner assignments.

Outputs

• Modeling spec (diagram, SQL pseudocode, dependencies).
• Test plan + configuration snippets.
• Deployment checklist with monitoring hooks and rollback instructions.
• Plan JSON entry stored/updated in .claude/plans for audit trail.

Agent/Skill Invocations

• analytics-modeling-lead – architects model + tests.
• quality-gates skill – ensures validation coverage.
• instrumentation skill – confirms data contracts stay intact.

GTM Agents Safeguards

• Fallback agents: document substitutes (e.g., BI Publisher covering modeling reviews) when specialists unavailable.
• Escalation triggers: if freshness, defect, or SLA guardrails breach twice within 24h, escalate to Data + RevOps leadership per GTM Agents runbook and consider rollback.
• Plan maintenance: update plan JSON whenever dependencies, owners, or deployment cadence changes, keeping audit alignment with GTM Agents standards.