From 78efa5c8ccf4ff444e121ee077ebad336a190123 Mon Sep 17 00:00:00 2001
From: Zhongwei Li <lizhongwei.nkcs@gmail.com>
Date: Sat, 29 Nov 2025 18:31:13 +0800
Subject: [PATCH] Initial commit

---
 .claude-plugin/plugin.json             | 24 ++++++++
 README.md                              |  3 +
 agents/customer-data-engineer.md       | 27 +++++++++
 agents/personalization-architect.md    | 30 ++++++++++
 agents/personalization-testing-lead.md | 27 +++++++++
 commands/configure-rules.md            | 49 ++++++++++++++++
 commands/define-profiles.md            | 48 ++++++++++++++++
 commands/monitor-personalization.md    | 48 ++++++++++++++++
 plugin.lock.json                       | 77 ++++++++++++++++++++++++++
 skills/content-variants/SKILL.md       | 30 ++++++++++
 skills/decision-trees/SKILL.md         | 30 ++++++++++
 skills/governance/SKILL.md             | 31 +++++++++++
 12 files changed, 424 insertions(+)
 create mode 100644 .claude-plugin/plugin.json
 create mode 100644 README.md
 create mode 100644 agents/customer-data-engineer.md
 create mode 100644 agents/personalization-architect.md
 create mode 100644 agents/personalization-testing-lead.md
 create mode 100644 commands/configure-rules.md
 create mode 100644 commands/define-profiles.md
 create mode 100644 commands/monitor-personalization.md
 create mode 100644 plugin.lock.json
 create mode 100644 skills/content-variants/SKILL.md
 create mode 100644 skills/decision-trees/SKILL.md
 create mode 100644 skills/governance/SKILL.md

diff --git a/.claude-plugin/plugin.json b/.claude-plugin/plugin.json
new file mode 100644
index 0000000..192ad8b
--- /dev/null
+++ b/.claude-plugin/plugin.json
@@ -0,0 +1,24 @@
+{
+  "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"
+  ]
+}
\ No newline at end of file
diff --git a/README.md b/README.md
new file mode 100644
index 0000000..5850d50
--- /dev/null
+++ b/README.md
@@ -0,0 +1,3 @@
+# personalization-engine
+
+Personalization orchestration covering profiles, decision rules, and governance
diff --git a/agents/customer-data-engineer.md b/agents/customer-data-engineer.md
new file mode 100644
index 0000000..72cf613
--- /dev/null
+++ b/agents/customer-data-engineer.md
@@ -0,0 +1,27 @@
+---
+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.
+
+---
diff --git a/agents/personalization-architect.md b/agents/personalization-architect.md
new file mode 100644
index 0000000..867c46d
--- /dev/null
+++ b/agents/personalization-architect.md
@@ -0,0 +1,30 @@
+---
+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.
+
+---
diff --git a/agents/personalization-testing-lead.md b/agents/personalization-testing-lead.md
new file mode 100644
index 0000000..ce60e53
--- /dev/null
+++ b/agents/personalization-testing-lead.md
@@ -0,0 +1,27 @@
+---
+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.
+
+---
diff --git a/commands/configure-rules.md b/commands/configure-rules.md
new file mode 100644
index 0000000..79204b0
--- /dev/null
+++ b/commands/configure-rules.md
@@ -0,0 +1,49 @@
+---
+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.
+
+---
diff --git a/commands/define-profiles.md b/commands/define-profiles.md
new file mode 100644
index 0000000..425227d
--- /dev/null
+++ b/commands/define-profiles.md
@@ -0,0 +1,48 @@
+---
+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.
+
+---
diff --git a/commands/monitor-personalization.md b/commands/monitor-personalization.md
new file mode 100644
index 0000000..dbe1592
--- /dev/null
+++ b/commands/monitor-personalization.md
@@ -0,0 +1,48 @@
+---
+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.
+
+---
diff --git a/plugin.lock.json b/plugin.lock.json
new file mode 100644
index 0000000..4260986
--- /dev/null
+++ b/plugin.lock.json
@@ -0,0 +1,77 @@
+{
+  "$schema": "internal://schemas/plugin.lock.v1.json",
+  "pluginId": "gh:gtmagents/gtm-agents:plugins/personalization-engine",
+  "normalized": {
+    "repo": null,
+    "ref": "refs/tags/v20251128.0",
+    "commit": "cf155475158ba805929ae32744e998e4c6bc34e0",
+    "treeHash": "6ee2a5616e94f6e408c6238200975b61a3b5d58faafa81b9d3d84363dcb3db29",
+    "generatedAt": "2025-11-28T10:17:18.815383Z",
+    "toolVersion": "publish_plugins.py@0.2.0"
+  },
+  "origin": {
+    "remote": "git@github.com:zhongweili/42plugin-data.git",
+    "branch": "master",
+    "commit": "aa1497ed0949fd50e99e70d6324a29c5b34f9390",
+    "repoRoot": "/Users/zhongweili/projects/openmind/42plugin-data"
+  },
+  "manifest": {
+    "name": "personalization-engine",
+    "description": "Personalization orchestration covering profiles, decision rules, and governance",
+    "version": "1.0.0"
+  },
+  "content": {
+    "files": [
+      {
+        "path": "README.md",
+        "sha256": "2e6cd800fd5b5ad376a2f0e2fd29726659bb9056efc4750cc16ca01b585f57f4"
+      },
+      {
+        "path": "agents/customer-data-engineer.md",
+        "sha256": "67bc8f87096a9cfa2a4143aeb233678ebe75ec0b8be87a39d83802b9924324ca"
+      },
+      {
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+        "sha256": "77716147a53e366ebafddadbaa75d70afa6ad4ab9778bc156a1e6e7d311bec9f"
+      },
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+      },
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+        "sha256": "96c548cd50bbf0a564ab1fbbcffc6b8a6adc9f4340ad25aaa32037c43f3b3ee4"
+      },
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+      },
+      {
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+        "sha256": "4a813ddf63c60095e9d1f83534392687a3b7d04df762077837f73bbfd9cd818d"
+      },
+      {
+        "path": "commands/define-profiles.md",
+        "sha256": "9646ca7e35686a6fde2c7326b65edf5dec99579ed2f263151afa776e0550730e"
+      },
+      {
+        "path": "skills/decision-trees/SKILL.md",
+        "sha256": "6b454adcf6fe8497440c32b7f83ddba0f1d6ecbd5556327e5793381022d8713d"
+      },
+      {
+        "path": "skills/content-variants/SKILL.md",
+        "sha256": "fb573a0ca07e3c6234b86c90118c927c76a8b0c38ee946e1bc3cb96f34a33f74"
+      },
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+      }
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+    "dirSha256": "6ee2a5616e94f6e408c6238200975b61a3b5d58faafa81b9d3d84363dcb3db29"
+  },
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+    "scannerVersion": null,
+    "flags": []
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+}
\ No newline at end of file
diff --git a/skills/content-variants/SKILL.md b/skills/content-variants/SKILL.md
new file mode 100644
index 0000000..772dbda
--- /dev/null
+++ b/skills/content-variants/SKILL.md
@@ -0,0 +1,30 @@
+---
+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.
+
+---
diff --git a/skills/decision-trees/SKILL.md b/skills/decision-trees/SKILL.md
new file mode 100644
index 0000000..41bb42d
--- /dev/null
+++ b/skills/decision-trees/SKILL.md
@@ -0,0 +1,30 @@
+---
+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.
+
+---
diff --git a/skills/governance/SKILL.md b/skills/governance/SKILL.md
new file mode 100644
index 0000000..de498fe
--- /dev/null
+++ b/skills/governance/SKILL.md
@@ -0,0 +1,31 @@
+---
+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.
+
+---