gh-gtmagents-gtm-agents-plugins-analytics-pipeline-orchestration/commands/define-events.md

name, description, usage

name	description	usage
define-events	Produces instrumentation specification with events, properties, owners, and QA steps.	/analytics-pipeline-orchestration:define-events --use_case "pipeline velocity" --sources "product,crm" --tools "Segment,dbt"

Command: define-events

Inputs

• use_case – business question or KPI the events support.
• sources – data sources involved (product, web, CRM, MAP, billing).
• tools – instrumentation stack (CDP, product analytics, warehouse, dbt).
• constraints – optional legal/compliance requirements.
• timeline – optional delivery date.

GTM Agents Pattern & Plan Checklist

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

• Pattern selection: Instrumentation typically runs pipeline (requirements → catalog → governance → QA → change mgmt). If governance + QA can run parallel, log a diamond segment with merge gate in the plan header.
• Plan schema: Save .claude/plans/plan-<timestamp>.json capturing objective, data sources, task IDs, dependencies, context passing (schemas, privacy notes), error handling, and success metrics (coverage %, defect ceiling).
• Tool hooks: Reference docs/gtm-essentials.md stack (Serena for repo diffs, Context7 for platform/legal docs, Sequential Thinking for review flows, Playwright for front-end event QA when applicable).
• Guardrails: Default retry limit = 2 for QA failures; escalation ladder = Analytics Data Strategist → Data Engineering Lead → RevOps.
• Review: Run docs/usage-guide.md#orchestration-best-practices-puerto-parity before execution to confirm agents, dependencies, deliverables.

Workflow

1. Requirement Gathering – clarify KPIs, dimensions, and downstream consumers.
2. Event Cataloging – list events, payloads, properties, IDs, sampling rate, ownership.
3. Governance Mapping – document naming conventions, consent handling, retention policies.
4. QA Plan – outline testing methods (unit tests, replay, observability dashboards).
5. Change Management – define review/approval steps, rollout plan, and version control.

Outputs

• Instrumentation spec (event name, description, properties, source, owner, status).
• Tracking plan (CSV/JSON/YAML) aligned with CDP or analytics tool requirements.
• QA checklist + evidence plan (logs, dashboards, sample payloads).
• Plan JSON entry stored/updated in .claude/plans for audit trail.

Agent/Skill Invocations

• analytics-data-strategist – leads requirements + governance.
• instrumentation skill – enforces schema + consent rules.
• quality-gates skill – defines QA expectations.

GTM Agents Safeguards

• Fallback agents: document substitutes (e.g., BI Publisher covering QA) if specialists unavailable.
• Escalation triggers: if instrumentation defects or compliance blockers breach guardrails twice in 48h, escalate to Data + Legal leadership, triggering GTM Agents-style rip-cord.
• Plan maintenance: update plan JSON/change log whenever events, schemas, or governance rules change to keep analytics audit-ready.

---