Initial commit

.claude-plugin/plugin.json

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+{
+  "name": "personalization-engine",
+  "description": "Personalization orchestration covering profiles, decision rules, and governance",
+  "version": "1.0.0",
+  "author": {
+    "name": "GTM Agents",
+    "email": "opensource@intentgpt.ai"
+  },
+  "skills": [
+    "./skills/decision-trees/SKILL.md",
+    "./skills/content-variants/SKILL.md",
+    "./skills/governance/SKILL.md"
+  ],
+  "agents": [
+    "./agents/personalization-architect.md",
+    "./agents/customer-data-engineer.md",
+    "./agents/personalization-testing-lead.md"
+  ],
+  "commands": [
+    "./commands/define-profiles.md",
+    "./commands/configure-rules.md",
+    "./commands/monitor-personalization.md"
+  ]
+}

README.md

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+# personalization-engine
+
+Personalization orchestration covering profiles, decision rules, and governance

agents/customer-data-engineer.md

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+---
+name: customer-data-engineer
+description: Builds and maintains the data pipelines powering personalization profiles and decisions.
+model: haiku
+---
+
+# Customer Data Engineer Agent
+
+## Responsibilities
+- Design ingestion + transformation flows for profile attributes, behavioral signals, and consent metadata.
+- Ensure identity resolution across product, marketing automation, CRM, and CDP systems.
+- Implement monitoring, data contracts, and backfill routines for personalization feeds.
+- Partner with architects and ops teams to deploy rule or model updates safely.
+
+## Workflow
+1. **Source Assessment** – audit upstream systems, schemas, refresh SLAs, and access controls.
+2. **Pipeline Design** – define transformations, matching logic, suppression rules, and storage targets.
+3. **Implementation** – configure ETL/dbt/CDP workflows, set version control, and run QA checks.
+4. **Deployment** – coordinate releases with MAP/product teams, document rollback paths.
+5. **Operations** – monitor latency, quality, and cost; schedule backfills or incident responses.
+
+## Outputs
+- Technical design doc (ERDs, DAGs, runbooks) for personalization data flows.
+- Data contract + validation suite results.
+- Monitoring dashboard snapshots with health status.
+
+---

agents/personalization-architect.md

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+---
+name: personalization-architect
+description: Designs profile schemas, decision flows, and experience frameworks for
+  personalization programs.
+model: sonnet
+---
+
+
+
+# Personalization Architect Agent
+
+## Responsibilities
+- Translate GTM goals into audience profiles, eligibility rules, and decision logic.
+- Map data sources, consent requirements, and activation endpoints across channels.
+- Align marketing, product, and RevOps teams on personalization roadmap + governance.
+- Maintain experimentation backlog with hypotheses tied to each decision branch.
+
+## Workflow
+1. **Brief Intake** – capture business objectives, KPIs, channels, and regulatory constraints.
+2. **Profile Blueprint** – define attributes, data sources, scoring logic, and freshness SLAs.
+3. **Decision Flow Design** – outline branching logic, fallback experiences, and guardrails.
+4. **Asset Planning** – document required content variants, creative briefs, and approval flows.
+5. **Measurement + QA** – specify success metrics, monitoring hooks, and regression tests.
+
+## Outputs
+- Personalization architecture deck (profiles, journeys, flows, dependencies).
+- Data + consent checklist with owners and refresh cadences.
+- Experiment roadmap mapped to decision points.
+
+---

agents/personalization-testing-lead.md

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+---
+name: personalization-testing-lead
+description: Plans and analyzes experiments for personalization experiences across channels.
+model: haiku
+---
+
+# Personalization Testing Lead Agent
+
+## Responsibilities
+- Design test matrices for profiles, rules, creative variants, and delivery channels.
+- Define guardrails, sample sizes, and success metrics for each decision branch.
+- Monitor experiments in-flight, pausing variants that risk revenue or compliance.
+- Translate insights into rollout plans and backlog updates with architects + ops teams.
+
+## Workflow
+1. **Hypothesis Intake** – gather objectives, affected segments, risk level, and constraints.
+2. **Experiment Design** – select methodology (A/B, multi-armed bandit, reinforcement), outline variables and KPIs.
+3. **Implementation Support** – provide MAP/CDP instructions, QA scripts, and logging requirements.
+4. **Monitoring & Governance** – watch performance, ensure ethics/compliance rules stay intact, escalate anomalies.
+5. **Insights Delivery** – create summaries, recommend rollouts or re-tests, feed learnings into decision tree updates.
+
+## Outputs
+- Experiment design brief (hypothesis, metrics, sample needs, guardrails).
+- Monitoring dashboard snapshot with interim reads.
+- Recommendations memo with rollout decision and next test backlog.
+
+---

commands/configure-rules.md

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+---
+name: configure-rules
+description: Deploys decision logic, content variants, and delivery rules across personalization channels.
+usage: /personalization-engine:configure-rules --initiative "PLG Onboarding" --environment staging --channels "web,in-app"
+---
+
+# Command: configure-rules
+
+## Inputs
+- **initiative** – reference to the personalization effort from `define-profiles`.
+- **environment** – staging | production to govern deployment steps.
+- **channels** – comma-separated list of activation surfaces.
+- **change_type** – net-new, update, rollback.
+- **approvers** – optional stakeholders for governance sign-off.
+
+### GTM Agents Pattern & Plan Checklist
+> Mirrors GTM Agents orchestrator blueprint @puerto/plugins/orchestrator/README.md#112-325.
+
+- **Pattern selection**: Rule configuration generally runs **pipeline** (pre-flight → decision build → variant mapping → QA → deployment). If decision build + variant prep happen in parallel, note a **diamond** block with merge gate in the plan header.
+- **Plan schema**: Save `.claude/plans/plan-<timestamp>.json` capturing initiative, environments, dependency graph (data eng, creative, QA, governance), error handling, and success metrics (latency, personalization lift, incident count).
+- **Tool hooks**: Reference `docs/gtm-essentials.md` stack—Serena for rule diffing, Context7 for platform SOPs, Sequential Thinking for go/no-go reviews, Playwright for simulation/QA evidence capture.
+- **Guardrails**: Default retry limit = 2 for deployment/QA failures; escalation ladder = Personalization Architect → Data Privacy Lead → Exec sponsor.
+- **Review**: Run `docs/usage-guide.md#orchestration-best-practices-puerto-parity` before deployment to confirm dependencies + approvals.
+
+## Workflow
+1. **Pre-flight Review** – validate profiles, data freshness, consent status, and experiment dependencies.
+2. **Decision Flow Build** – configure rules, weights, or model endpoints in MAP/CDP/product tooling.
+3. **Variant Mapping** – link each rule outcome to content assets, CTAs, and fallback experiences.
+4. **QA & Simulation** – run synthetic traffic through decision trees, capture screenshots/logs.
+5. **Deployment & Logging** – push changes via API/CLI, note version metadata, set up monitoring hooks.
+
+## Outputs
+- Deployment runbook with rule IDs, version numbers, and rollback plan.
+- QA evidence (simulation results, screenshots, payload logs).
+- Governance log including approvers, timestamps, and linked experiments.
+- Plan JSON entry stored/updated in `.claude/plans` for audit trail.
+
+## Agent/Skill Invocations
+- `customer-data-engineer` – ensures data pipelines and environments are ready.
+- `personalization-architect` – verifies experience logic + content mapping.
+- `content-variants` skill – tracks asset requirements + approvals.
+- `governance` skill – enforces change controls and compliance steps.
+
+## GTM Agents Safeguards
+- **Fallback agents**: document substitutes (e.g., governance lead covering architect) when owners unavailable.
+- **Escalation triggers**: if QA fails twice, latency spikes, or privacy gate blocks deployment, trigger GTM Agents rip-cord and log remediation in plan JSON.
+- **Plan maintenance**: update plan JSON/change log when rule sets, environments, or deployment windows change so reviewers can trace history.
+
+---

commands/define-profiles.md

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+---
+name: define-profiles
+description: Produces audience profile schemas, data sources, and activation requirements for personalization programs.
+usage: /personalization-engine:define-profiles --initiative "PLG Onboarding" --channels "web,in-app,email"
+---
+
+# Command: define-profiles
+
+## Inputs
+- **initiative** – program or campaign name anchoring the personalization effort.
+- **channels** – comma-separated channels to activate (web, in-app, email, ads, sales).
+- **metrics** – optional KPIs (activation rate, pipeline $, retention).
+- **constraints** – optional compliance, consent, or tooling notes.
+- **timeline** – optional delivery window.
+
+### GTM Agents Pattern & Plan Checklist
+> Mirrors GTM Agents orchestrator blueprint @puerto/plugins/orchestrator/README.md#112-325.
+
+- **Pattern selection**: Profile definition typically runs **diamond** (objective intake ↔ attribute inventory in parallel, reconverging into activation/governance) or **pipeline** when sequential; document pattern choice in plan header.
+- **Plan schema**: Save `.claude/plans/plan-<timestamp>.json` capturing initiative, data sources, dependency graph (data eng, legal, privacy), error handling, and success metrics (attribute coverage %, consent integrity, activation lift).
+- **Tool hooks**: Reference `docs/gtm-essentials.md` stack—Serena for schema diffs, Context7 for privacy/compliance docs, Sequential Thinking for governance reviews, Playwright for consent/opt-in flow QA if needed.
+- **Guardrails**: Default retry limit = 2 for data pulls or consent checks; escalation ladder = Personalization Architect → Data Privacy Lead → Exec sponsor.
+- **Review**: Run `docs/usage-guide.md#orchestration-best-practices-puerto-parity` before finalizing to confirm dependencies + approvals.
+
+## Workflow
+1. **Objective Intake** – clarify business goals, target personas, lifecycle stages.
+2. **Attribute Inventory** – list required fields, source systems, refresh cadence, and consent rules.
+3. **Profile Definition** – outline segments, eligibility logic, scoring, decay windows.
+4. **Activation Mapping** – document downstream systems, API/webhook needs, fallback states.
+5. **Governance Plan** – assign owners, QA cadences, and change management checkpoints.
+
+## Outputs
+- Profile schema deck/table (attributes, types, source, SLA, privacy notes).
+- Eligibility + suppression logic doc for each profile.
+- Activation checklist linking profiles to channels and tooling.
+- Plan JSON entry stored/updated in `.claude/plans` for audit trail.
+
+## Agent/Skill Invocations
+- `personalization-architect` – leads objectives + profile design.
+- `customer-data-engineer` – validates data feasibility.
+- `decision-trees` skill – ensures logic structures align with downstream rules.
+
+## GTM Agents Safeguards
+- **Fallback agents**: document substitutes (e.g., Customer Data Engineer covering Architect) when leads unavailable.
+- **Escalation triggers**: escalate if consent/compliance blockers occur twice or attribute coverage misses SLA; log remediation in plan JSON.
+- **Plan maintenance**: update plan JSON/change log when attributes, data sources, or governance cadences change.
+
+---

commands/monitor-personalization.md

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+---
+name: monitor-personalization
+description: Audits personalization performance, governance compliance, and experiment results.
+usage: /personalization-engine:monitor-personalization --initiative "PLG Onboarding" --window 14d --detail full
+---
+
+# Command: monitor-personalization
+
+## Inputs
+- **initiative** – personalization program or campaign to analyze.
+- **window** – time frame (7d, 14d, 30d) for pulling metrics.
+- **detail** – summary | full to control report depth.
+- **dimension** – optional breakdown (profile, channel, cohort).
+- **alert_threshold** – optional KPI threshold to trigger incident items.
+
+### GTM Agents Pattern & Plan Checklist
+> Mirrors GTM Agents orchestrator blueprint @puerto/plugins/orchestrator/README.md#112-325.
+
+- **Pattern selection**: Monitoring usually runs **pipeline** (data aggregation → governance scan → experiment readout → issue detection → action plan). If governance + experiments review can run concurrently, capture a **diamond** block with merge gate in the plan header.
+- **Plan schema**: Save `.claude/plans/plan-<timestamp>.json` capturing initiative, data feeds, dependency graph (data eng, privacy, experimentation), error handling, and success metrics (lift %, incident response time, consent adherence).
+- **Tool hooks**: Reference `docs/gtm-essentials.md` stack—Serena for schema diffs, Context7 for governance/experiment SOPs, Sequential Thinking for retro cadence, Playwright for experience QA evidence.
+- **Guardrails**: Default retry limit = 2 for failed data pulls or anomaly jobs; escalation ladder = Testing Lead → Personalization Architect → Data Privacy Lead.
+- **Review**: Run `docs/usage-guide.md#orchestration-best-practices-puerto-parity` before distribution to ensure dependencies + approvals are logged.
+
+## Workflow
+1. **Data Aggregation** – pull engagement, conversion, and revenue impact by profile/channel plus decision tree health signals.
+2. **Governance Scan** – verify consent flags, fallback rates, and rule change logs for compliance.
+3. **Experiment Readout** – summarize live/completed tests with statistical confidence and recommended actions.
+4. **Issue Detection** – flag anomalies (data freshness, variant suppression, performance dips) and suggest playbooks.
+5. **Report Distribution** – publish recap with dashboards, backlog items, and owners.
+
+## Outputs
+- Performance dashboard snapshot segmented by profile/channel/variant.
+- Governance checklist status with any violations or pending approvals.
+- Experiment memo with next steps + rollout guidance.
+- Plan JSON entry stored/updated in `.claude/plans` for audit trail.
+
+## Agent/Skill Invocations
+- `testing-lead` – interprets experiments and recommends rollouts.
+- `personalization-architect` – validates experience integrity.
+- `governance` skill – enforces policy checks and approvals.
+
+## GTM Agents Safeguards
+- **Fallback agents**: document substitutes (e.g., Governance covering Testing Lead) when leads unavailable.
+- **Escalation triggers**: escalate if alert_threshold breached twice, consent violations appear, or anomaly alerts repeat; log remediation steps in plan JSON.
+- **Plan maintenance**: update plan JSON/change log when metrics, thresholds, or monitoring cadences change to keep audits accurate.
+
+---

plugin.lock.json

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skills/content-variants/SKILL.md

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+---
+name: content-variants
+description: Use when planning, approving, and versioning personalized creative assets.
+---
+
+# Content Variant System Skill
+
+## When to Use
+- Mapping creative requirements for each decision tree branch.
+- Coordinating design, copy, and legal reviews across multiple channels.
+- Auditing variant performance or sunsetting outdated experiences.
+
+## Framework
+1. **Variant Inventory** – catalog base asset, variant name, audience, channel, owner, expiration.
+2. **Approval Flow** – document reviewers, compliance steps, localization, accessibility requirements.
+3. **Asset Delivery** – link storage locations (DAM, CMS, MAP) plus version IDs and CDN paths.
+4. **Testing Hooks** – note experiment IDs, KPIs, guardrails for each variant.
+5. **Lifecycle Management** – set refresh cadences, archival rules, and dependency tracking.
+
+## Templates
+- Variant matrix (channel × persona × lifecycle stage).
+- Approval checklist (copy, design, legal, localization, accessibility).
+- Performance tracker (variant → impressions → engagement → conversion → decision).
+
+## Tips
+- Assign unique IDs to every variant for analytics + rollback references.
+- Bundle variants into kits aligned with key journeys for easier governance.
+- Pair with `decision-trees` outputs to ensure every branch has an approved asset.
+
+---

skills/decision-trees/SKILL.md

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+---
+name: decision-trees
+description: Use when designing branching logic, eligibility rules, and fallback paths.
+---
+
+# Personalization Decision Trees Skill
+
+## When to Use
+- Planning logic for dynamic experiences across web, in-app, email, or sales plays.
+- Auditing existing decision flows for complexity, coverage, or compliance gaps.
+- Simulating new branches before deploying rule or model updates.
+
+## Framework
+1. **Objective Mapping** – tie each node to business KPIs and user intents.
+2. **Signal Hierarchy** – prioritize deterministic signals (consent, account tier, lifecycle) before behavioral or predictive ones.
+3. **Fallback Design** – ensure every branch has a safe default when data is missing or risk flags appear.
+4. **Experiment Hooks** – embed test slots at key decision points with guardrail metrics.
+5. **Monitoring** – log path selections, success rates, and anomaly alerts for continuous tuning.
+
+## Templates
+- Decision tree canvas (node, condition, action, fallback, owner).
+- Signal priority matrix (signal → freshness → reliability → privacy risk).
+- Simulation checklist (scenarios, expected path, validation steps).
+
+## Tips
+- Keep trees shallow where possible; offload complexity to scoring models or external services.
+- Version control decision logic alongside content assets for traceability.
+- Pair with `governance` skill to log approvals for high-impact branches.
+
+---

skills/governance/SKILL.md

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+---
+name: governance
+description: Use to enforce approvals, compliance, and auditability for personalization
+  programs.
+---
+
+# Personalization Governance Skill
+
+## When to Use
+- Deploying or updating personalization rules, models, or high-impact content variants.
+- Running quarterly audits on consent, data usage, or fairness metrics.
+- Investigating incidents related to personalization errors or policy breaches.
+
+## Framework
+1. **Policy Alignment** – document legal, privacy, accessibility, and ethical constraints per channel.
+2. **Approval Workflow** – define RACI (architect, legal, security, marketing) and required evidence per change.
+3. **Change Logging** – capture version metadata (who, what, when, why), including rollback steps.
+4. **Risk Monitoring** – set KPIs + alerts for fairness, bias, consent violations, or performance regressions.
+5. **Audit Trail** – maintain dashboards + storage for decision logs, approvals, and incident reports.
+
+## Templates
+- Change request form (summary, impact, risk score, approvers, attachments).
+- Governance checklist (consent, accessibility, localization, security, QA evidence).
+- Incident review template (root cause, remediation, follow-up actions, owner).
+
+## Tips
+- Pair governance checkpoints with CI/CD or deployment scripts to prevent bypass.
+- Use unique change IDs to connect decision tree updates with content variants and experiments.
+- Schedule quarterly tabletop exercises to keep stakeholders fluent in escalation paths.
+
+---