feat(ms-ai-architect): add plugin to open marketplace (v1.5.0 baseline)

Initial addition of ms-ai-architect plugin to the open-source marketplace. Private content excluded: orchestrator/ (Linear tooling), docs/utredning/ (client investigation), generated test reports and PDF export script. skill-gen tooling moved from orchestrator/ to scripts/skill-gen/. Security scan: WARNING (risk 20/100) — no secrets, no injection found. False positive fixed: added gitleaks:allow to Python variable reference in output-validation-grounding-verification.md line 109. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-04-07 17:17:17 +02:00 · 2026-04-07 17:17:17 +02:00 · 6a7632146e
commit 6a7632146e
parent a8d79e4484
490 changed files with 213249 additions and 2 deletions
--- a/plugins/ms-ai-architect/scripts/export-pdf.py
+++ b/plugins/ms-ai-architect/scripts/export-pdf.py
@ -0,0 +1,211 @@
+#!/usr/bin/env python3
+"""
+Generate a professional PDF from a markdown file.
+
+Requirements:
+    pip install markdown weasyprint
+
+Usage:
+    python scripts/export-pdf.py <input.md> [output.pdf]
+
+If output is not specified, uses the same name as input with .pdf extension.
+"""
+
+import re
+import sys
+from pathlib import Path
+
+import markdown
+from weasyprint import HTML
+
+# --- CSS ---
+
+CSS = """
+@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&display=swap');
+
+@page {
+    size: A4;
+    margin: 25mm 20mm 25mm 20mm;
+
+    @bottom-center {
+        content: counter(page);
+        font-family: 'Inter', system-ui, -apple-system, 'Segoe UI', sans-serif;
+        font-size: 8pt;
+        color: #718096;
+    }
+}
+
+@page :first {
+    @bottom-center { content: none; }
+}
+
+* { box-sizing: border-box; }
+
+body {
+    font-family: 'Inter', system-ui, -apple-system, 'Segoe UI', Roboto, sans-serif;
+    font-size: 10.5pt;
+    line-height: 1.6;
+    color: #1a202c;
+    max-width: 100%;
+}
+
+h1 {
+    font-size: 20pt;
+    font-weight: 700;
+    color: #1a365d;
+    margin-top: 32px;
+    margin-bottom: 12px;
+    page-break-after: avoid;
+}
+
+h2 {
+    font-size: 15pt;
+    font-weight: 700;
+    color: #1a365d;
+    margin-top: 28px;
+    margin-bottom: 10px;
+    padding-bottom: 6px;
+    border-bottom: 2px solid #e2e8f0;
+    page-break-after: avoid;
+}
+
+h3 {
+    font-size: 12pt;
+    font-weight: 600;
+    color: #2b6cb0;
+    margin-top: 20px;
+    margin-bottom: 8px;
+    page-break-after: avoid;
+}
+
+h4 {
+    font-size: 10.5pt;
+    font-weight: 600;
+    color: #2d3748;
+    margin-top: 16px;
+    margin-bottom: 6px;
+}
+
+table {
+    width: 100%;
+    border-collapse: collapse;
+    margin: 12px 0 20px 0;
+    font-size: 9pt;
+    page-break-inside: auto;
+}
+
+thead { display: table-header-group; }
+tr { page-break-inside: avoid; }
+
+th {
+    background-color: #2b6cb0;
+    color: white;
+    font-weight: 600;
+    text-align: left;
+    padding: 8px 10px;
+    font-size: 8.5pt;
+    text-transform: uppercase;
+    letter-spacing: 0.3px;
+}
+
+td {
+    padding: 7px 10px;
+    border-bottom: 1px solid #e2e8f0;
+    vertical-align: top;
+}
+
+tr:nth-child(even) td { background-color: #f7fafc; }
+
+blockquote {
+    border-left: 3px solid #2b6cb0;
+    margin: 12px 0;
+    padding: 8px 16px;
+    background: #ebf8ff;
+    color: #2a4365;
+    font-size: 10pt;
+    border-radius: 0 4px 4px 0;
+}
+
+code {
+    background: #edf2f7;
+    padding: 1px 4px;
+    border-radius: 3px;
+    font-size: 9pt;
+    font-family: 'SF Mono', 'Fira Code', 'Consolas', monospace;
+}
+
+hr {
+    border: none;
+    border-top: 2px solid #e2e8f0;
+    margin: 24px 0;
+}
+
+ul, ol { margin: 8px 0 12px 0; padding-left: 24px; }
+li { margin-bottom: 4px; }
+strong { font-weight: 600; color: #1a202c; }
+a { color: #2b6cb0; text-decoration: none; }
+p { margin: 8px 0; }
+
+.section-break { page-break-before: always; }
+.score-high { color: #276749; font-weight: 700; }
+.score-medium { color: #d69e2e; font-weight: 700; }
+.score-low { color: #c53030; font-weight: 700; }
+"""
+
+
+def postprocess_html(html: str) -> str:
+    """Add CSS classes for scores and risk levels."""
+    # Section breaks on h2 (except first)
+    h2_count = 0
+
+    def add_section_break(match: re.Match) -> str:
+        nonlocal h2_count
+        h2_count += 1
+        if h2_count > 1:
+            return f'<h2 class="section-break">{match.group(1)}</h2>'
+        return match.group(0)
+
+    html = re.sub(r"<h2>(.*?)</h2>", add_section_break, html)
+
+    # Score coloring: 4/5, 5/5 green; 3/5 yellow; 1/5, 2/5 red
+    html = re.sub(r"<td>([45])/5</td>", r'<td><span class="score-high">\1/5</span></td>', html)
+    html = re.sub(r"<td>3/5</td>", '<td><span class="score-medium">3/5</span></td>', html)
+    html = re.sub(r"<td>([12])/5</td>", r'<td><span class="score-low">\1/5</span></td>', html)
+
+    return html
+
+
+def main() -> None:
+    if len(sys.argv) < 2:
+        print("Usage: python export-pdf.py <input.md> [output.pdf]")
+        sys.exit(1)
+
+    input_path = Path(sys.argv[1])
+    if not input_path.exists():
+        print(f"Error: {input_path} not found")
+        sys.exit(1)
+
+    output_path = Path(sys.argv[2]) if len(sys.argv) > 2 else input_path.with_suffix(".pdf")
+
+    md_text = input_path.read_text(encoding="utf-8")
+    body_html = markdown.markdown(md_text, extensions=["tables", "smarty", "sane_lists"])
+    body_html = postprocess_html(body_html)
+
+    full_html = f"""<!DOCTYPE html>
+<html lang="no">
+<head>
+    <meta charset="UTF-8">
+    <style>{CSS}</style>
+</head>
+<body>
+    {body_html}
+</body>
+</html>"""
+
+    HTML(string=full_html).write_pdf(str(output_path))
+    print(f"PDF generated: {output_path}")
+    print(f"Size: {output_path.stat().st_size / 1024:.1f} KB")
+
+
+if __name__ == "__main__":
+    main()
--- a/plugins/ms-ai-architect/scripts/kb-staleness-check.sh
+++ b/plugins/ms-ai-architect/scripts/kb-staleness-check.sh
@ -0,0 +1,235 @@
+#!/bin/bash
+# kb-staleness-check.sh — Scan knowledge base files for staleness
+# Usage: bash scripts/kb-staleness-check.sh [--days N] [--priority-only] [--verbose] [--json] [--output FILE]
+#
+# Default threshold: 90 days
+# Priority order: prices > compliance > features > architecture
+
+set -euo pipefail
+
+PLUGIN_ROOT="$(cd "$(dirname "$0")/.." && pwd)"
+# Scan all skill reference directories
+KB_ROOTS=(
+  "$PLUGIN_ROOT/skills/ms-ai-advisor/references"
+  "$PLUGIN_ROOT/skills/ms-ai-governance/references"
+  "$PLUGIN_ROOT/skills/ms-ai-security/references"
+  "$PLUGIN_ROOT/skills/ms-ai-engineering/references"
+  "$PLUGIN_ROOT/skills/ms-ai-infrastructure/references"
+)
+
+# Defaults
+THRESHOLD_DAYS=90
+PRIORITY_ONLY=false
+VERBOSE=false
+JSON_OUTPUT=false
+OUTPUT_FILE=""
+
+# Parse arguments
+while [[ $# -gt 0 ]]; do
+  case "$1" in
+    --days)
+      THRESHOLD_DAYS="$2"
+      shift 2
+      ;;
+    --priority-only)
+      PRIORITY_ONLY=true
+      shift
+      ;;
+    --verbose)
+      VERBOSE=true
+      shift
+      ;;
+    --json)
+      JSON_OUTPUT=true
+      shift
+      ;;
+    --output)
+      OUTPUT_FILE="$2"
+      shift 2
+      ;;
+    *)
+      echo "Unknown option: $1"
+      echo "Usage: bash scripts/kb-staleness-check.sh [--days N] [--priority-only] [--verbose] [--json] [--output FILE]"
+      exit 1
+      ;;
+  esac
+done
+
+for kb_dir in "${KB_ROOTS[@]}"; do
+  if [ ! -d "$kb_dir" ]; then
+    echo "WARNING: Knowledge base directory not found: $kb_dir" >&2
+  fi
+done
+
+NOW=$(date +%s)
+TOTAL=0
+FRESH=0
+STALE=0
+STALE_CRITICAL=0
+STALE_HIGH=0
+STALE_MEDIUM=0
+STALE_LOW=0
+
+# Collect stale files for sorted summary
+declare -a STALE_ENTRIES=()
+
+get_priority() {
+  local filepath="$1"
+  local lower_path
+  lower_path=$(echo "$filepath" | tr '[:upper:]' '[:lower:]')
+
+  # Critical (30 days): cost, pricing, pris
+  if echo "$lower_path" | grep -qE '(cost|pricing|pris)'; then
+    echo "Critical:30"
+    return
+  fi
+
+  # High (60 days): compliance, security, governance
+  if echo "$lower_path" | grep -qE '(responsible-ai|norwegian-public-sector-governance|ai-security-engineering)'; then
+    echo "High:60"
+    return
+  fi
+
+  # Medium (90 days): platforms, features, extensibility
+  if echo "$lower_path" | grep -qE '(platforms|copilot-extensibility|azure-ai-services|multi-modal|performance-scalability|monitoring-observability|agent-orchestration|data-engineering|api-management|hybrid-edge|bcdr|rag-architecture|mlops-genaiops|prompt-engineering)'; then
+    echo "Medium:90"
+    return
+  fi
+
+  # Low (180 days): architecture, development, patterns
+  echo "Low:180"
+}
+
+for KB_ROOT in "${KB_ROOTS[@]}"; do
+  [ -d "$KB_ROOT" ] || continue
+  while IFS= read -r -d '' file; do
+    TOTAL=$((TOTAL + 1))
+
+    # macOS-compatible stat for modification time
+    MOD_EPOCH=$(stat -f '%m' "$file" 2>/dev/null || stat -c '%Y' "$file" 2>/dev/null)
+    DAYS_OLD=$(( (NOW - MOD_EPOCH) / 86400 ))
+
+    REL_PATH="${file#"$KB_ROOT/"}"
+    PRIORITY_INFO=$(get_priority "$REL_PATH")
+    PRIORITY="${PRIORITY_INFO%%:*}"
+    PRIORITY_THRESHOLD="${PRIORITY_INFO##*:}"
+
+    if [ "$DAYS_OLD" -gt "$PRIORITY_THRESHOLD" ]; then
+      STALE=$((STALE + 1))
+      case "$PRIORITY" in
+        Critical) STALE_CRITICAL=$((STALE_CRITICAL + 1)) ;;
+        High)     STALE_HIGH=$((STALE_HIGH + 1)) ;;
+        Medium)   STALE_MEDIUM=$((STALE_MEDIUM + 1)) ;;
+        Low)      STALE_LOW=$((STALE_LOW + 1)) ;;
+      esac
+
+      FULL_REL="${file#"$PLUGIN_ROOT/"}"
+      if [ "$JSON_OUTPUT" = true ]; then
+        echo "[STALE] $REL_PATH — ${DAYS_OLD} days old (threshold: ${PRIORITY_THRESHOLD}) — Priority: $PRIORITY" >&2
+      else
+        echo "[STALE] $REL_PATH — ${DAYS_OLD} days old (threshold: ${PRIORITY_THRESHOLD}) — Priority: $PRIORITY"
+      fi
+      STALE_ENTRIES+=("${DAYS_OLD}:${PRIORITY}:${FULL_REL}")
+    else
+      FRESH=$((FRESH + 1))
+      if [ "$VERBOSE" = true ] && [ "$PRIORITY_ONLY" = false ]; then
+        if [ "$JSON_OUTPUT" = true ]; then
+          echo "[FRESH] $REL_PATH — ${DAYS_OLD} days old (threshold: ${PRIORITY_THRESHOLD}) — Priority: $PRIORITY" >&2
+        else
+          echo "[FRESH] $REL_PATH — ${DAYS_OLD} days old (threshold: ${PRIORITY_THRESHOLD}) — Priority: $PRIORITY"
+        fi
+      fi
+    fi
+  done < <(find "$KB_ROOT" -name '*.md' -type f -print0)
+done
+
+# JSON output mode
+if [ "$JSON_OUTPUT" = true ]; then
+  JSON="{"
+  JSON+="\"generated_at\":\"$(date -Iseconds)\","
+  JSON+="\"total\":$TOTAL,"
+  JSON+="\"fresh\":$FRESH,"
+  JSON+="\"stale\":$STALE,"
+  JSON+="\"stale_by_priority\":{\"critical\":$STALE_CRITICAL,\"high\":$STALE_HIGH,\"medium\":$STALE_MEDIUM,\"low\":$STALE_LOW},"
+  JSON+="\"files\":["
+
+  FIRST=true
+  for entry in "${STALE_ENTRIES[@]}"; do
+    days="${entry%%:*}"
+    rest="${entry#*:}"
+    priority="${rest%%:*}"
+    filepath="${rest#*:}"
+
+    # Determine skill from path
+    skill="unknown"
+    case "$filepath" in
+      *ms-ai-advisor*) skill="ms-ai-advisor" ;;
+      *ms-ai-engineering*) skill="ms-ai-engineering" ;;
+      *ms-ai-governance*) skill="ms-ai-governance" ;;
+      *ms-ai-security*) skill="ms-ai-security" ;;
+      *ms-ai-infrastructure*) skill="ms-ai-infrastructure" ;;
+    esac
+
+    # Determine category from path
+    category=$(echo "$filepath" | sed -E 's|.*/references/([^/]+)/.*|\1|')
+
+    if [ "$FIRST" = true ]; then
+      FIRST=false
+    else
+      JSON+=","
+    fi
+    JSON+="{\"path\":\"$filepath\",\"skill\":\"$skill\",\"category\":\"$category\",\"age_days\":$days,\"priority\":\"$priority\"}"
+  done
+
+  JSON+="]}"
+
+  if [ -n "$OUTPUT_FILE" ]; then
+    echo "$JSON" > "$OUTPUT_FILE"
+    echo "JSON written to: $OUTPUT_FILE" >&2
+  else
+    echo "$JSON"
+  fi
+  exit 0
+fi
+
+echo ""
+echo "=== KB Freshness Report ==="
+echo "Total files: $TOTAL"
+echo "Fresh: $FRESH"
+echo "Stale: $STALE (Critical: $STALE_CRITICAL, High: $STALE_HIGH, Medium: $STALE_MEDIUM, Low: $STALE_LOW)"
+
+if [ "$STALE" -gt 0 ]; then
+  echo ""
+  echo "Recommended update order:"
+
+  # Sort stale entries: Critical first, then High, Medium, Low; within priority by age descending
+  PRIORITY_ORDER="Critical High Medium Low"
+  INDEX=1
+
+  for prio in $PRIORITY_ORDER; do
+    # Collect entries for this priority, sort by age descending
+    PRIO_ENTRIES=()
+    for entry in "${STALE_ENTRIES[@]}"; do
+      entry_prio="${entry#*:}"
+      entry_prio="${entry_prio%%:*}"
+      if [ "$entry_prio" = "$prio" ]; then
+        PRIO_ENTRIES+=("$entry")
+      fi
+    done
+
+    # Sort by days (first field) descending
+    if [ ${#PRIO_ENTRIES[@]} -gt 0 ]; then
+      SORTED=$(printf '%s\n' "${PRIO_ENTRIES[@]}" | sort -t: -k1 -nr)
+      while IFS= read -r sorted_entry; do
+        days="${sorted_entry%%:*}"
+        rest="${sorted_entry#*:}"
+        rest="${rest#*:}"
+        echo "  ${INDEX}. [$prio] $rest (${days} days)"
+        INDEX=$((INDEX + 1))
+      done <<< "$SORTED"
+    fi
+  done
+fi
+
+echo ""
+echo "Run with --verbose to see fresh files. Use --days N to override threshold. Use --json for machine-readable output."
--- a/plugins/ms-ai-architect/scripts/skill-gen/categories.json
+++ b/plugins/ms-ai-architect/scripts/skill-gen/categories.json
@ -0,0 +1,406 @@
+{
+  "version": "1.0",
+  "created": "2026-02-03",
+  "target_dir": "skills/ms-ai-engineering/references",
+  "total_estimated_skills": "300-350",
+  "waves": [
+    {
+      "wave": 1,
+      "priority": "HIGH",
+      "description": "Kritisk manglende kunnskap for enterprise AI-arkitektur",
+      "categories": [
+        "azure-ai-services",
+        "rag-architecture",
+        "responsible-ai",
+        "copilot-extensibility",
+        "prompt-engineering",
+        "cost-optimization",
+        "mlops-genaiops"
+      ]
+    },
+    {
+      "wave": 1.5,
+      "priority": "HIGH",
+      "description": "Utredningsstøtte: norsk offentlig sektor, AI-sikkerhet og observerbarhet",
+      "categories": [
+        "norwegian-public-sector-governance",
+        "ai-security-engineering",
+        "monitoring-observability"
+      ]
+    },
+    {
+      "wave": 2,
+      "priority": "MEDIUM",
+      "description": "Verdifulle tillegg for komplett arkitekturdekning",
+      "categories": [
+        "agent-orchestration",
+        "bcdr",
+        "data-engineering",
+        "api-management",
+        "hybrid-edge",
+        "multi-modal",
+        "performance-scalability"
+      ]
+    }
+  ],
+  "categories": {
+    "azure-ai-services": {
+      "name": "Azure AI Services (Foundry Tools)",
+      "dir": "azure-ai-services",
+      "priority": "HIGH",
+      "description": "Pre-bygde AI-tjenester: Vision, Speech, Language, Document Intelligence, Translator, Content Understanding. Fundamentale byggeblokker for enterprise AI.",
+      "estimated_skills": 20,
+      "examples": [
+        "azure-ai-vision-overview",
+        "document-intelligence-models",
+        "speech-services-architecture",
+        "language-services-text-analytics",
+        "content-understanding-multimodal",
+        "translator-custom-models",
+        "azure-ai-search-indexing",
+        "custom-vision-vs-florence",
+        "ai-services-networking-security",
+        "ai-services-pricing-optimization"
+      ],
+      "existing_overlap": ["platforms/azure-ai-foundry.md"],
+      "notes": "Foundry Tools er ny branding (2025). Unngå duplikering med azure-ai-foundry.md som dekker overordnet plattform."
+    },
+    "rag-architecture": {
+      "name": "RAG Architecture & Semantic Search",
+      "dir": "rag-architecture",
+      "priority": "HIGH",
+      "description": "Retrieval-Augmented Generation med Azure AI Search. Vektorindeksering, embedding, hybrid search, reranking, chunking, citation tracking.",
+      "estimated_skills": 22,
+      "examples": [
+        "rag-architecture-patterns",
+        "azure-ai-search-vector-indexing",
+        "embedding-model-selection",
+        "chunking-strategies",
+        "hybrid-search-configuration",
+        "semantic-ranker-optimization",
+        "rag-evaluation-metrics",
+        "multi-index-federation",
+        "rag-security-rbac",
+        "graphrag-knowledge-graphs"
+      ],
+      "existing_overlap": ["architecture/decision-trees.md"],
+      "notes": "RAG er det vanligste mønsteret for enterprise AI. Detaljer er planlagt som ms-rag-architect plugin men grunnleggende arkitektur dekkes her."
+    },
+    "responsible-ai": {
+      "name": "Responsible AI & Governance",
+      "dir": "responsible-ai",
+      "priority": "HIGH",
+      "description": "Microsofts Responsible AI-rammeverk, AI-etikk, bias-deteksjon, forklarbarhet, GDPR/AI Act compliance, AI governance for offentlig sektor.",
+      "estimated_skills": 22,
+      "examples": [
+        "responsible-ai-framework-overview",
+        "ai-act-compliance-guide",
+        "bias-detection-mitigation",
+        "model-explainability-techniques",
+        "ai-governance-structure",
+        "ai-center-of-excellence",
+        "red-teaming-ai-models",
+        "content-safety-implementation",
+        "ai-impact-assessment",
+        "transparency-documentation"
+      ],
+      "existing_overlap": ["architecture/security.md", "architecture/public-sector-checklist.md"],
+      "notes": "Utfyller security.md (teknisk sikkerhet) med governance og compliance. Spesielt viktig for offentlig sektor etter AI Act."
+    },
+    "copilot-extensibility": {
+      "name": "Copilot Extensibility & Integration",
+      "dir": "copilot-extensibility",
+      "priority": "HIGH",
+      "description": "Utvidelse av M365 Copilot og Copilot Studio: declarative agents, custom engine agents, plugins, connectors, Graph API, MCP.",
+      "estimated_skills": 22,
+      "examples": [
+        "declarative-agents-overview",
+        "custom-engine-agents",
+        "copilot-studio-topics-entities",
+        "graph-api-for-copilot",
+        "copilot-connectors-patterns",
+        "mcp-integration-copilot-studio",
+        "copilot-analytics-usage",
+        "teams-copilot-extensions",
+        "sharepoint-agents",
+        "copilot-studio-dlp-governance"
+      ],
+      "existing_overlap": ["platforms/copilot-studio.md", "platforms/m365-copilot.md"],
+      "notes": "Går dypere enn eksisterende plattformfiler. Fokus på implementeringsmønstre, ikke overordnet arkitektur."
+    },
+    "prompt-engineering": {
+      "name": "Prompt Engineering & LLM Optimization",
+      "dir": "prompt-engineering",
+      "priority": "HIGH",
+      "description": "System message design, few-shot/zero-shot teknikker, chain-of-thought, reasoning-modeller (O1/O3), grounding, output-formatering.",
+      "estimated_skills": 18,
+      "examples": [
+        "system-message-design-patterns",
+        "few-shot-learning-techniques",
+        "chain-of-thought-prompting",
+        "reasoning-models-o1-o3",
+        "structured-output-json-mode",
+        "function-calling-patterns",
+        "grounding-with-search",
+        "temperature-and-sampling",
+        "token-optimization-techniques",
+        "prompt-testing-evaluation"
+      ],
+      "existing_overlap": [],
+      "notes": "Helt nytt område. Direkte påvirkning på kvaliteten av alle AI-løsninger."
+    },
+    "cost-optimization": {
+      "name": "Cost Optimization & FinOps for AI",
+      "dir": "cost-optimization",
+      "priority": "HIGH",
+      "description": "Token-optimalisering, caching, reserved capacity, modellvalg, Azure Cost Management, chargeback, budsjettplanlegging for AI.",
+      "estimated_skills": 20,
+      "examples": [
+        "token-cost-optimization",
+        "semantic-caching-patterns",
+        "reserved-capacity-planning",
+        "model-selection-price-performance",
+        "azure-cost-management-ai",
+        "ptu-vs-paygo-decision",
+        "ai-builder-credits-transition",
+        "cost-allocation-chargeback",
+        "budget-forecasting-ai",
+        "small-language-models-cost"
+      ],
+      "existing_overlap": ["architecture/cost-models.md"],
+      "notes": "Utfyller cost-models.md med dypere strategier. cost-models.md dekker prislister, dette dekker optimaliseringsteknikker."
+    },
+    "mlops-genaiops": {
+      "name": "MLOps & GenAIOps",
+      "dir": "mlops-genaiops",
+      "priority": "HIGH",
+      "description": "CI/CD for AI, modellmonitorering, versjonshåndtering, A/B-testing, retraining, evaluering, Azure ML pipelines for produksjon.",
+      "estimated_skills": 22,
+      "examples": [
+        "genaiops-overview",
+        "azure-ml-pipelines",
+        "model-versioning-registry",
+        "llm-evaluation-framework",
+        "ab-testing-ai-models",
+        "data-drift-monitoring",
+        "automated-retraining",
+        "ci-cd-ai-models",
+        "prompt-flow-production",
+        "model-deployment-strategies"
+      ],
+      "existing_overlap": [],
+      "notes": "Helt nytt område. Kritisk for å gå fra prototyp til produksjon."
+    },
+    "data-engineering": {
+      "name": "Data Engineering for AI",
+      "dir": "data-engineering",
+      "priority": "MEDIUM",
+      "description": "Dataintegrasjon med Microsoft Fabric, Data Factory, OneLake, Databricks. Zero-ETL, lakehouse-arkitektur, AI-drevet dataintegrering.",
+      "estimated_skills": 22,
+      "examples": [
+        "microsoft-fabric-for-ai",
+        "onelake-data-strategy",
+        "data-factory-ai-pipelines",
+        "zero-etl-patterns",
+        "data-quality-for-ai",
+        "real-time-streaming-ai",
+        "dataverse-ai-integration",
+        "data-lakehouse-architecture",
+        "data-governance-purview",
+        "synthetic-data-generation"
+      ],
+      "existing_overlap": [],
+      "notes": "Datakvalitet er #1 årsak til AI-prosjektfeil. Microsoft Fabric er raskt voksende."
+    },
+    "api-management": {
+      "name": "API Management & AI Gateway",
+      "dir": "api-management",
+      "priority": "MEDIUM",
+      "description": "Azure API Management som AI-gateway: rate limiting, token quota, load balancing, circuit breaker, autentisering, multi-region.",
+      "estimated_skills": 18,
+      "examples": [
+        "apim-ai-gateway-overview",
+        "token-rate-limiting",
+        "load-balancing-openai",
+        "circuit-breaker-patterns",
+        "multi-region-gateway",
+        "apim-authentication-patterns",
+        "backend-pool-management",
+        "streaming-support-apim",
+        "cost-tracking-apim",
+        "apim-vs-direct-access"
+      ],
+      "existing_overlap": [],
+      "notes": "Viktig for enterprise-skalering. APIM AI Gateway er relativt nytt (2024-2025)."
+    },
+    "hybrid-edge": {
+      "name": "Hybrid Cloud & Edge AI",
+      "dir": "hybrid-edge",
+      "priority": "MEDIUM",
+      "description": "Azure Arc, Azure Local, IoT Operations, edge AI inferencing, disconnected scenarios, datasuverenitet for offentlig sektor.",
+      "estimated_skills": 18,
+      "examples": [
+        "azure-arc-ai-management",
+        "azure-local-ai-workloads",
+        "edge-ai-inferencing",
+        "disconnected-ai-scenarios",
+        "data-sovereignty-patterns",
+        "iot-operations-ai",
+        "hybrid-rag-architecture",
+        "on-premises-llm-deployment",
+        "azure-confidential-computing",
+        "sovereign-cloud-norway"
+      ],
+      "existing_overlap": [],
+      "notes": "Spesielt relevant for norsk offentlig sektor med suverenitetskrav og sikkerhetsgradert informasjon."
+    },
+    "bcdr": {
+      "name": "Business Continuity & Disaster Recovery",
+      "dir": "bcdr",
+      "priority": "MEDIUM",
+      "description": "HA, DR og BCDR for AI: multi-region, backup, failover, RTO/RPO for Azure OpenAI og AI Foundry.",
+      "estimated_skills": 16,
+      "examples": [
+        "multi-region-azure-openai",
+        "ai-foundry-dr-planning",
+        "backup-recovery-strategies",
+        "failover-testing-ai",
+        "rto-rpo-ai-services",
+        "data-replication-patterns",
+        "geo-redundancy-search",
+        "incident-response-ai",
+        "capacity-planning-dr",
+        "compliance-bcdr-requirements"
+      ],
+      "existing_overlap": [],
+      "notes": "Nødvendig for kritiske produksjonssystemer i offentlig sektor."
+    },
+    "multi-modal": {
+      "name": "Multi-Modal AI",
+      "dir": "multi-modal",
+      "priority": "MEDIUM",
+      "description": "Tekst + bilde + tale + video: GPT-4V/GPT-5 vision, Video Indexer, Speech-integrasjon, multi-modal RAG, aksessibilitet.",
+      "estimated_skills": 18,
+      "examples": [
+        "gpt-vision-architecture",
+        "video-indexer-ai",
+        "multi-modal-rag",
+        "speech-to-ai-pipelines",
+        "image-generation-dall-e",
+        "document-vision-processing",
+        "accessibility-multi-modal",
+        "real-time-audio-api",
+        "video-analysis-patterns",
+        "multi-modal-evaluation"
+      ],
+      "existing_overlap": [],
+      "notes": "Økende etterspørsel etter multi-modale løsninger. GPT-5 styrker vision-kapabiliteter."
+    },
+    "agent-orchestration": {
+      "name": "Agent Orchestration & Automation",
+      "dir": "agent-orchestration",
+      "priority": "MEDIUM",
+      "description": "Multi-agent systemer, orkesteringsmønstre, agent-kommunikasjon, Agent 365, Semantic Kernel/Agent Framework-mønstre.",
+      "estimated_skills": 20,
+      "examples": [
+        "multi-agent-patterns",
+        "agent-orchestration-topologies",
+        "agent-to-agent-communication",
+        "agent-365-governance",
+        "semantic-kernel-agents",
+        "agent-memory-patterns",
+        "tool-use-patterns",
+        "agent-evaluation-testing",
+        "human-in-the-loop-agents",
+        "autonomous-workflow-patterns"
+      ],
+      "existing_overlap": ["development/agent-framework.md"],
+      "notes": "Utfyller agent-framework.md med orkestrerings- og designmønstre."
+    },
+    "performance-scalability": {
+      "name": "Performance & Scalability",
+      "dir": "performance-scalability",
+      "priority": "MEDIUM",
+      "description": "Latency-reduksjon, throughput, caching, batching, streaming, auto-scaling, CDN for AI-workloads.",
+      "estimated_skills": 18,
+      "examples": [
+        "latency-optimization-openai",
+        "streaming-responses-patterns",
+        "batch-api-usage",
+        "auto-scaling-ai-infra",
+        "cdn-edge-caching-ai",
+        "connection-pooling-patterns",
+        "throughput-optimization",
+        "model-distillation-perf",
+        "async-processing-patterns",
+        "load-testing-ai-services"
+      ],
+      "existing_overlap": [],
+      "notes": "Viktig for brukeropplevelse. Komplementerer cost-optimization."
+    },
+    "monitoring-observability": {
+      "name": "Monitoring & Observability",
+      "dir": "monitoring-observability",
+      "priority": "HIGH",
+      "description": "Azure Monitor, Application Insights, Log Analytics for AI. Token tracking, anomaly detection, dashboards, alerting.",
+      "estimated_skills": 18,
+      "examples": [
+        "azure-monitor-ai-workloads",
+        "application-insights-llm",
+        "token-usage-tracking",
+        "anomaly-detection-ai",
+        "custom-ai-dashboards",
+        "alerting-strategies-ai",
+        "distributed-tracing-ai",
+        "log-analytics-ai-queries",
+        "sla-monitoring-ai",
+        "cost-attribution-monitoring"
+      ],
+      "existing_overlap": [],
+      "notes": "Nødvendig for produksjonsoperasjoner. Komplementerer MLOps."
+    },
+    "norwegian-public-sector-governance": {
+      "name": "Norwegian Public Sector AI Governance",
+      "dir": "norwegian-public-sector-governance",
+      "priority": "HIGH",
+      "description": "Norsk lovverk, Digdir-rammeverk og forvaltningsmetodikk anvendt på AI. Utredningsinstruksen, Digdirs 7 arkitekturprinsipper, rammeverk for digital samhandling (EIF), DPIA, ROS-analyse, NSM grunnprinsipper, anskaffelser og gevinstrealisering for AI i offentlig sektor.",
+      "estimated_skills": 20,
+      "research_sources": ["websearch", "regjeringen.no", "lovdata.no", "digdir.no", "nsm.no", "datatilsynet.no"],
+      "examples": [
+        "utredningsinstruksen-methodology",
+        "forvaltningsloven-ai-decisions",
+        "digdir-principle-1-user-centric",
+        "digdir-principle-4-trust",
+        "digital-samhandling-5-layers",
+        "dpia-norwegian-methodology",
+        "ros-analyse-ai-systems",
+        "nsm-grunnprinsipper-ai-mapping",
+        "anskaffelser-ai-procurement",
+        "gevinstrealisering-ai-projects"
+      ],
+      "existing_overlap": ["architecture/public-sector-checklist.md", "architecture/ai-utredning-template.md"],
+      "notes": "Fundamentalt annerledes enn øvrige kategorier: primærkilder er regjeringen.no, lovdata.no, digdir.no, nsm.no — IKKE microsoft-learn. Innhold er regulatorisk/juridisk, ikke teknisk produktdokumentasjon. Prompt-template må bruke WebSearch for norske kilder i tillegg til microsoft-learn MCP."
+    },
+    "ai-security-engineering": {
+      "name": "AI Security Engineering",
+      "dir": "ai-security-engineering",
+      "priority": "HIGH",
+      "description": "Operasjonell AI-sikkerhet: prompt injection forsvar, jailbreak-prevention, content safety kalibrering, PII-deteksjon, trusselmodellering, sikkerhetsscoring, hendelseshåndtering, output-validering, zero trust for AI, datalekkasjeforebygging og red teaming.",
+      "estimated_skills": 15,
+      "examples": [
+        "prompt-injection-defense-patterns",
+        "jailbreak-prevention-production",
+        "content-safety-filter-calibration",
+        "pii-detection-norwegian-text",
+        "ai-threat-modeling-stride",
+        "security-scoring-rubric-6dimensions",
+        "ai-incident-response-procedures",
+        "output-validation-grounding-verification",
+        "zero-trust-ai-services",
+        "ai-red-team-operations-practical"
+      ],
+      "existing_overlap": ["architecture/security.md", "responsible-ai/red-teaming-ai-models.md", "responsible-ai/content-safety-implementation.md", "prompt-engineering/adversarial-prompting-and-jailbreaks.md"],
+      "notes": "Komplementerer responsible-ai (governance/teori) og prompt-engineering (angrepsteknikker) med OPERASJONELLE forsvarsmønstre. Fokus: forsvar, deteksjon, respons — ikke policy eller angrep."
+    }
+  }
+}
--- a/plugins/ms-ai-architect/scripts/skill-gen/category-skill-map.json
+++ b/plugins/ms-ai-architect/scripts/skill-gen/category-skill-map.json
@ -0,0 +1,32 @@
+{
+  "version": "1.0",
+  "description": "Maps KB categories to their target skill directories",
+  "mapping": {
+    "rag-architecture": "ms-ai-engineering",
+    "azure-ai-services": "ms-ai-engineering",
+    "copilot-extensibility": "ms-ai-engineering",
+    "prompt-engineering": "ms-ai-engineering",
+    "data-engineering": "ms-ai-engineering",
+    "api-management": "ms-ai-engineering",
+    "agent-orchestration": "ms-ai-engineering",
+    "multi-modal": "ms-ai-engineering",
+    "mlops-genaiops": "ms-ai-engineering",
+    "performance-scalability": "ms-ai-engineering",
+    "monitoring-observability": "ms-ai-engineering",
+    "responsible-ai": "ms-ai-governance",
+    "norwegian-public-sector-governance": "ms-ai-governance",
+    "cost-optimization": "ms-ai-security",
+    "ai-security-engineering": "ms-ai-security",
+    "security-scoring": "ms-ai-security",
+    "hybrid-edge": "ms-ai-infrastructure",
+    "bcdr": "ms-ai-infrastructure",
+    "platforms": "ms-ai-advisor",
+    "architecture": "ms-ai-advisor"
+  },
+  "priority_thresholds": {
+    "critical": 30,
+    "high": 60,
+    "medium": 90,
+    "low": 180
+  }
+}
--- a/plugins/ms-ai-architect/scripts/skill-gen/expand-categories.sh
+++ b/plugins/ms-ai-architect/scripts/skill-gen/expand-categories.sh
@ -0,0 +1,301 @@
+#!/bin/bash
+# expand-categories.sh — Expand skill categories into full manifest
+#
+# Uses claude --print to expand each category in categories.json
+# into 15-25 individual skill titles, producing manifest.json
+#
+# Usage:
+#   ./expand-categories.sh                    # Expand all categories
+#   ./expand-categories.sh azure-ai-services  # Expand single category
+#   ./expand-categories.sh --wave 1           # Expand wave 1 only
+#
+# Prerequisites:
+#   - claude CLI installed and authenticated
+#   - jq installed
+#   - categories.json in same directory
+
+set -euo pipefail
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+PLUGIN_DIR="$(cd "$SCRIPT_DIR/../.." && pwd)"
+CATEGORIES_FILE="$SCRIPT_DIR/categories.json"
+MANIFEST_FILE="$SCRIPT_DIR/manifest.json"
+LOG_DIR="$SCRIPT_DIR/logs"
+
+# Model for expansion (haiku is sufficient for generating titles)
+MODEL="${MODEL:-haiku}"
+
+# Colors
+RED='\033[0;31m'
+GREEN='\033[0;32m'
+YELLOW='\033[1;33m'
+BLUE='\033[0;34m'
+NC='\033[0m'
+
+log() { echo -e "${BLUE}[expand]${NC} $1" >&2; }
+success() { echo -e "${GREEN}[expand]${NC} $1" >&2; }
+warn() { echo -e "${YELLOW}[expand]${NC} $1" >&2; }
+error() { echo -e "${RED}[expand]${NC} $1" >&2; }
+
+# Check prerequisites
+check_prereqs() {
+    if ! command -v claude &>/dev/null; then
+        error "claude CLI not found. Install: npm install -g @anthropic-ai/claude-code"
+        exit 1
+    fi
+    if ! command -v jq &>/dev/null; then
+        error "jq not found. Install: brew install jq"
+        exit 1
+    fi
+    if [[ ! -f "$CATEGORIES_FILE" ]]; then
+        error "categories.json not found at $CATEGORIES_FILE"
+        exit 1
+    fi
+}
+
+# Get list of existing reference files for context
+get_existing_refs() {
+    local category_dir="$1"
+    local refs_dir="$PLUGIN_DIR/skills/ms-ai-engineering/references"
+
+    # List all existing reference files
+    find "$refs_dir" -name "*.md" -type f 2>/dev/null | while read -r f; do
+        basename "$f" .md
+    done | sort | tr '\n' ', '
+}
+
+# Expand a single category
+expand_category() {
+    local category_key="$1"
+
+    local name description estimated examples existing_overlap notes
+    name=$(jq -r ".categories[\"$category_key\"].name" "$CATEGORIES_FILE")
+    description=$(jq -r ".categories[\"$category_key\"].description" "$CATEGORIES_FILE")
+    estimated=$(jq -r ".categories[\"$category_key\"].estimated_skills" "$CATEGORIES_FILE")
+    examples=$(jq -r ".categories[\"$category_key\"].examples | join(\", \")" "$CATEGORIES_FILE")
+    existing_overlap=$(jq -r ".categories[\"$category_key\"].existing_overlap | join(\", \")" "$CATEGORIES_FILE")
+    notes=$(jq -r ".categories[\"$category_key\"].notes" "$CATEGORIES_FILE")
+
+    local existing_refs
+    existing_refs=$(get_existing_refs "$category_key")
+
+    log "Expanding: $name ($estimated skills estimated)"
+
+    local prompt
+    prompt="Du er en Microsoft AI Solution Architect som planlegger en kunnskapsbase.
+
+Kategorien **${name}** trenger individuelle kunnskapsfiler (skills).
+
+## Kategori-beskrivelse
+${description}
+
+## Eksisterende filer i kunnskapsbasen (unngå duplikering)
+${existing_refs}
+
+## Eksisterende overlapp å ta hensyn til
+${existing_overlap}
+
+## Eksempel-titler (for inspirasjon, ikke begrens deg til disse)
+${examples}
+
+## Notater
+${notes}
+
+## Oppgave
+
+Generer en JSON-array med NØYAKTIG ${estimated} skills for denne kategorien.
+
+Hver skill skal ha:
+- \`id\`: kebab-case filnavn (uten .md)
+- \`title\`: Engelsk tittel (kortfattet, beskrivende)
+- \`description\`: 1-2 setninger på norsk om hva filen dekker
+- \`subtopics\`: 3-5 viktige undertemaer som array
+
+Regler:
+1. Ikke dupliser emner som allerede finnes i eksisterende filer
+2. Sørg for bred dekning uten overlapp mellom skills
+3. Titler skal være spesifikke (\"Azure AI Vision OCR and Document Processing\", ikke bare \"Vision\")
+4. Prioriter mest nyttige emner for enterprise AI-arkitekter i norsk offentlig sektor
+5. Returner KUN valid JSON-array, ingen annen tekst
+
+Eksempel-format:
+[
+  {
+    \"id\": \"example-skill-name\",
+    \"title\": \"Example Skill - Full Descriptive Title\",
+    \"description\": \"Beskrivelse av hva denne kunnskapsfilen dekker.\",
+    \"subtopics\": [\"subtopic-1\", \"subtopic-2\", \"subtopic-3\"]
+  }
+]"
+
+    local output
+    output=$(claude --print --model "$MODEL" "$prompt" 2>"$LOG_DIR/expand-${category_key}.err")
+
+    # Extract JSON array from response (handles markdown code blocks, plain JSON, etc.)
+    local json_output
+    json_output=$(python3 -c "
+import sys, json, re
+text = sys.stdin.read()
+# Try to find JSON array in code blocks first
+m = re.search(r'\`\`\`(?:json)?\s*(\[[\s\S]*?\])\s*\`\`\`', text)
+if m:
+    arr = json.loads(m.group(1))
+    print(json.dumps(arr))
+    sys.exit(0)
+# Try to find bare JSON array
+m = re.search(r'(\[[\s\S]*\])', text)
+if m:
+    try:
+        arr = json.loads(m.group(1))
+        print(json.dumps(arr))
+        sys.exit(0)
+    except: pass
+# Nothing found
+sys.exit(1)
+" <<< "$output" 2>/dev/null)
+
+    # Validate JSON
+    if ! echo "$json_output" | jq . &>/dev/null; then
+        error "Invalid JSON for $category_key. Raw output saved to $LOG_DIR/expand-${category_key}.raw"
+        echo "$output" > "$LOG_DIR/expand-${category_key}.raw"
+        return 1
+    fi
+
+    local count
+    count=$(echo "$json_output" | jq 'length')
+    success "$name: $count skills generated"
+
+    # Return the JSON
+    echo "$json_output"
+}
+
+# Build or update manifest
+build_manifest() {
+    local categories_to_expand=("$@")
+
+    # Initialize manifest if it doesn't exist
+    if [[ ! -f "$MANIFEST_FILE" ]]; then
+        echo '{"version":"1.0","created":"'"$(date +%Y-%m-%d)"'","categories":{}}' | jq . > "$MANIFEST_FILE"
+    fi
+
+    local total=0
+    local failed=0
+
+    for category_key in "${categories_to_expand[@]}"; do
+        local skills_json
+        if skills_json=$(expand_category "$category_key"); then
+            # Add to manifest
+            local dir
+            dir=$(jq -r ".categories[\"$category_key\"].dir" "$CATEGORIES_FILE")
+            local name
+            name=$(jq -r ".categories[\"$category_key\"].name" "$CATEGORIES_FILE")
+            local priority
+            priority=$(jq -r ".categories[\"$category_key\"].priority" "$CATEGORIES_FILE")
+
+            local category_obj
+            category_obj=$(jq -n \
+                --arg name "$name" \
+                --arg dir "$dir" \
+                --arg priority "$priority" \
+                --argjson skills "$skills_json" \
+                '{name: $name, dir: $dir, priority: $priority, skills: $skills}')
+
+            # Merge into manifest
+            jq --arg key "$category_key" --argjson cat "$category_obj" \
+                '.categories[$key] = $cat' "$MANIFEST_FILE" > "$MANIFEST_FILE.tmp" \
+                && mv "$MANIFEST_FILE.tmp" "$MANIFEST_FILE"
+
+            local count
+            count=$(echo "$skills_json" | jq 'length')
+            total=$((total + count))
+        else
+            failed=$((failed + 1))
+        fi
+
+        # Rate limiting: pause between API calls
+        sleep 2
+    done
+
+    echo "" >&2
+    log "═══════════════════════════════════════"
+    success "Total skills in manifest: $total"
+    [[ $failed -gt 0 ]] && error "Failed categories: $failed"
+    log "Manifest: $MANIFEST_FILE"
+    log "═══════════════════════════════════════"
+}
+
+# Parse arguments
+parse_args() {
+    local wave=""
+    local single_category=""
+
+    while [[ $# -gt 0 ]]; do
+        case "$1" in
+            --wave)
+                wave="$2"
+                shift 2
+                ;;
+            --model)
+                MODEL="$2"
+                shift 2
+                ;;
+            --help|-h)
+                echo "Usage: $0 [category-key] [--wave N] [--model MODEL]"
+                echo ""
+                echo "Options:"
+                echo "  category-key    Expand single category"
+                echo "  --wave N        Expand all categories in wave N (1 or 2)"
+                echo "  --model MODEL   Claude model to use (default: haiku)"
+                echo ""
+                echo "Examples:"
+                echo "  $0                          # Expand all categories"
+                echo "  $0 azure-ai-services        # Expand single category"
+                echo "  $0 --wave 1                 # Expand HIGH priority only"
+                exit 0
+                ;;
+            *)
+                single_category="$1"
+                shift
+                ;;
+        esac
+    done
+
+    # Determine which categories to expand
+    if [[ -n "$single_category" ]]; then
+        echo "$single_category"
+    elif [[ -n "$wave" ]]; then
+        jq -r ".waves[] | select(.wave == $wave) | .categories[]" "$CATEGORIES_FILE"
+    else
+        jq -r '.categories | keys[]' "$CATEGORIES_FILE"
+    fi
+}
+
+# Main
+main() {
+    check_prereqs
+    mkdir -p "$LOG_DIR"
+
+    log "Skill Category Expansion"
+    log "Model: $MODEL | Categories file: $CATEGORIES_FILE"
+    echo "" >&2
+
+    local categories=()
+    while IFS= read -r line; do
+        categories+=("$line")
+    done < <(parse_args "$@")
+
+    if [[ ${#categories[@]} -eq 0 ]]; then
+        error "No categories to expand"
+        exit 1
+    fi
+
+    log "Categories to expand: ${#categories[@]}"
+    for cat in "${categories[@]}"; do
+        log "  - $cat"
+    done
+    echo "" >&2
+
+    build_manifest "${categories[@]}"
+}
+
+main "$@"
--- a/plugins/ms-ai-architect/scripts/skill-gen/generate-skills.sh
+++ b/plugins/ms-ai-architect/scripts/skill-gen/generate-skills.sh
@ -0,0 +1,610 @@
+#!/bin/bash
+# generate-skills.sh — Generate knowledge reference files from manifest
+#
+# Reads manifest.json and generates each skill file using claude --print
+# with the prompt template. Supports resuming from where it left off.
+#
+# Usage:
+#   ./generate-skills.sh                          # Generate all pending skills
+#   ./generate-skills.sh --category rag-architecture  # Generate single category
+#   ./generate-skills.sh --skill azure-ai-vision-overview  # Generate single skill
+#   ./generate-skills.sh --wave 1                 # Generate wave 1 (HIGH) only
+#   ./generate-skills.sh --dry-run                # Show what would be generated
+#   ./generate-skills.sh --pilot 5                # Generate first N skills only
+#
+# Prerequisites:
+#   - claude CLI installed and authenticated
+#   - jq installed
+#   - manifest.json (run expand-categories.sh first)
+
+set -euo pipefail
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+PLUGIN_DIR="$(cd "$SCRIPT_DIR/../.." && pwd)"
+REFS_DIR="$PLUGIN_DIR/skills/ms-ai-engineering/references"
+MANIFEST_FILE="$SCRIPT_DIR/manifest.json"
+STATE_FILE="$SCRIPT_DIR/state.json"
+PROMPT_TEMPLATE="$SCRIPT_DIR/prompt-template.md"
+CATEGORIES_FILE="$SCRIPT_DIR/categories.json"
+LOG_DIR="$SCRIPT_DIR/logs"
+
+# Model for generation (sonnet for quality, haiku for speed)
+MODEL="${MODEL:-sonnet}"
+
+# Limits
+PARALLEL="${PARALLEL:-1}"       # Sequential by default for reliability
+DELAY="${DELAY:-3}"             # Seconds between API calls
+MIN_SIZE="${MIN_SIZE:-5000}"    # Minimum file size in bytes (quality gate)
+MAX_RETRIES="${MAX_RETRIES:-2}" # Retries for failed/small files
+
+# Flags
+DRY_RUN=false
+PILOT=0
+
+# Colors
+RED='\033[0;31m'
+GREEN='\033[0;32m'
+YELLOW='\033[1;33m'
+BLUE='\033[0;34m'
+CYAN='\033[0;36m'
+NC='\033[0m'
+
+log() { echo -e "${BLUE}[gen]${NC} $1" >&2; }
+success() { echo -e "${GREEN}[gen]${NC} $1" >&2; }
+warn() { echo -e "${YELLOW}[gen]${NC} $1" >&2; }
+error() { echo -e "${RED}[gen]${NC} $1" >&2; }
+detail() { echo -e "${CYAN}[gen]${NC} $1" >&2; }
+
+# Check prerequisites
+check_prereqs() {
+    if ! command -v claude &>/dev/null; then
+        error "claude CLI not found"
+        exit 1
+    fi
+    if ! command -v jq &>/dev/null; then
+        error "jq not found"
+        exit 1
+    fi
+    if [[ ! -f "$MANIFEST_FILE" ]]; then
+        error "manifest.json not found. Run expand-categories.sh first."
+        exit 1
+    fi
+}
+
+# Initialize or load state
+init_state() {
+    if [[ ! -f "$STATE_FILE" ]]; then
+        jq -n '{
+            "started": "'$(date -Iseconds)'",
+            "completed": [],
+            "failed": [],
+            "skipped": [],
+            "stats": {
+                "total_generated": 0,
+                "total_failed": 0,
+                "total_skipped": 0,
+                "total_bytes": 0
+            }
+        }' > "$STATE_FILE"
+    fi
+}
+
+# Check if skill is already completed
+is_completed() {
+    local skill_id="$1"
+    jq -e --arg id "$skill_id" '.completed | index($id) != null' "$STATE_FILE" &>/dev/null
+}
+
+# Mark skill as completed
+mark_completed() {
+    local skill_id="$1"
+    local file_size="$2"
+    jq --arg id "$skill_id" --arg size "$file_size" '
+        .completed += [$id] |
+        .stats.total_generated += 1 |
+        .stats.total_bytes += ($size | tonumber)
+    ' "$STATE_FILE" > "$STATE_FILE.tmp" && mv "$STATE_FILE.tmp" "$STATE_FILE"
+}
+
+# Mark skill as failed
+mark_failed() {
+    local skill_id="$1"
+    local reason="$2"
+    jq --arg id "$skill_id" --arg reason "$reason" '
+        .failed += [{"id": $id, "reason": $reason, "time": (now | todate)}]  |
+        .stats.total_failed += 1
+    ' "$STATE_FILE" > "$STATE_FILE.tmp" && mv "$STATE_FILE.tmp" "$STATE_FILE"
+}
+
+# Get existing context for a category (overlap files content summary)
+get_existing_context() {
+    local category_key="$1"
+    local overlaps
+    overlaps=$(jq -r ".categories[\"$category_key\"].existing_overlap // [] | .[]" "$CATEGORIES_FILE" 2>/dev/null)
+
+    if [[ -z "$overlaps" ]]; then
+        echo "Ingen direkte overlapp med eksisterende filer."
+        return
+    fi
+
+    local context=""
+    for overlap in $overlaps; do
+        local filepath="$REFS_DIR/$overlap"
+        if [[ -f "$filepath" ]]; then
+            # Extract just the header and section titles
+            local summary
+            summary=$(head -50 "$filepath" | grep -E '^#{1,3} ' | head -10)
+            context+="**$overlap:** $summary"$'\n'
+        fi
+    done
+
+    echo "${context:-Ingen direkte overlapp med eksisterende filer.}"
+}
+
+# Get related skills in same category
+get_related_skills() {
+    local category_key="$1"
+    local current_skill="$2"
+
+    jq -r --arg key "$category_key" --arg current "$current_skill" '
+        .categories[$key].skills[]
+        | select(.id != $current)
+        | "- \(.title): \(.description)"
+    ' "$MANIFEST_FILE" | head -20
+}
+
+# Build the prompt for a specific skill
+build_prompt() {
+    local category_key="$1"
+    local skill_id="$2"
+
+    local title description subtopics
+    title=$(jq -r --arg key "$category_key" --arg id "$skill_id" \
+        '.categories[$key].skills[] | select(.id == $id) | .title' "$MANIFEST_FILE")
+    description=$(jq -r --arg key "$category_key" --arg id "$skill_id" \
+        '.categories[$key].skills[] | select(.id == $id) | .description' "$MANIFEST_FILE")
+    subtopics=$(jq -r --arg key "$category_key" --arg id "$skill_id" \
+        '.categories[$key].skills[] | select(.id == $id) | .subtopics | join(", ")' "$MANIFEST_FILE")
+
+    local category_name category_description
+    category_name=$(jq -r --arg key "$category_key" '.categories[$key].name' "$MANIFEST_FILE")
+    category_description=$(jq -r --arg key "$category_key" '.categories[$key].name' "$CATEGORIES_FILE")
+
+    local existing_context
+    existing_context=$(get_existing_context "$category_key")
+
+    local related_skills
+    related_skills=$(get_related_skills "$category_key" "$skill_id")
+
+    # Build the full prompt from template
+    cat <<PROMPT
+Du er Cosmo Skyberg, en senior Microsoft AI Solution Architect som skriver kunnskapsreferanser for et Claude Code-plugin. Referansene brukes av en AI-arkitekt persona som hjelper norske organisasjoner (spesielt offentlig sektor) med Microsoft AI-løsninger.
+
+## Oppgave
+
+Skriv en komplett kunnskapsreferanse om: **${title}**
+
+Skill-beskrivelse: ${description}
+Viktige undertemaer å dekke: ${subtopics}
+
+Denne filen tilhører kategorien **${category_name}**.
+
+## Format-krav (STRENGT)
+
+### Header
+\`\`\`markdown
+# ${title}
+
+**Last updated:** 2026-02
+**Status:** [GA | Preview | Announced]
+**Category:** ${category_name}
+
+---
+\`\`\`
+
+### Innhold (7-15 KB, alle seksjoner påkrevd)
+
+1. **Introduksjon** (2-3 avsnitt)
+   - Hva er dette? Hvorfor er det viktig for enterprise AI?
+   - Plassering i Microsoft-økosystemet
+   - Norsk prosa, engelske tekniske termer
+
+2. **Kjernekomponenter / Nøkkelegenskaper**
+   - Bruk tabeller for sammenligninger
+   - Bullet points for egenskaper
+   - Kodeeksempler der relevant (korte, illustrative)
+
+3. **Arkitekturmønstre**
+   - 2-3 typiske bruksmønstre
+   - Når bruke hvert mønster
+   - Fordeler og ulemper
+
+4. **Beslutningsveiledning**
+   - "Velg X når..." beslutningstabell
+   - Vanlige feil og misforståelser
+   - Røde flagg arkitekten bør se etter
+
+5. **Integrasjon med Microsoft-stakken**
+   - Hvordan dette kobles til andre Azure/M365-tjenester
+   - Typiske integrasjonsmønstre
+
+6. **Offentlig sektor (Norge)**
+   - GDPR, Schrems II, AI Act, Forvaltningsloven
+   - Datasuverenitet og residency
+
+7. **Kostnad og lisensiering**
+   - Prismodell (oversikt)
+   - Kostnadsoptimaliseringstips
+
+8. **For arkitekten (Cosmo)**
+   - 5-8 nøkkelspørsmål å stille kunden
+   - Vanlige fallgruver
+   - Anbefalinger per modenhetsnivå
+
+9. **Kilder og verifisering**
+   - Microsoft Learn-referanser
+   - Konfidensnivå (Verified / Baseline / Assumed)
+
+## Regler
+
+1. Norsk prosa, engelske tekniske termer
+2. Tabeller over tekst for sammenligninger
+3. Konkret over vagt — spesifikke tall og tjenester
+4. Balansert — vis fordeler OG ulemper
+5. Oppdatert — 2025-2026 informasjon
+6. Størrelse: 7-15 KB (200-400 linjer)
+7. Ikke dupliser: ${existing_context}
+
+## Relaterte skills (for kryssreferanser)
+${related_skills}
+
+Skriv KUN markdown-innholdet. Ingen innledende forklaring eller avsluttende kommentar.
+PROMPT
+}
+
+# Generate a single skill file
+generate_skill() {
+    local category_key="$1"
+    local skill_id="$2"
+    local attempt="${3:-1}"
+
+    local category_dir
+    category_dir=$(jq -r --arg key "$category_key" '.categories[$key].dir' "$MANIFEST_FILE")
+
+    local output_dir="$REFS_DIR/$category_dir"
+    local output_file="$output_dir/$skill_id.md"
+
+    local title
+    title=$(jq -r --arg key "$category_key" --arg id "$skill_id" \
+        '.categories[$key].skills[] | select(.id == $id) | .title' "$MANIFEST_FILE")
+
+    # Skip if already completed
+    if is_completed "$skill_id"; then
+        detail "  Skipping (already completed): $skill_id"
+        return 0
+    fi
+
+    # Skip if file already exists and is large enough
+    if [[ -f "$output_file" ]]; then
+        local existing_size
+        existing_size=$(wc -c < "$output_file" | tr -d ' ')
+        if [[ $existing_size -ge $MIN_SIZE ]]; then
+            detail "  Skipping (file exists, ${existing_size}B): $skill_id"
+            mark_completed "$skill_id" "$existing_size"
+            return 0
+        fi
+        warn "  File exists but too small (${existing_size}B < ${MIN_SIZE}B), regenerating: $skill_id"
+    fi
+
+    if $DRY_RUN; then
+        log "  [DRY RUN] Would generate: $output_file"
+        log "  Title: $title"
+        return 0
+    fi
+
+    log "  Generating ($attempt/$((MAX_RETRIES+1))): $title"
+
+    # Create output directory
+    mkdir -p "$output_dir"
+
+    # Build prompt
+    local prompt
+    prompt=$(build_prompt "$category_key" "$skill_id")
+
+    # Generate with claude --print
+    local output
+    if ! output=$(claude --print --model "$MODEL" "$prompt" 2>"$LOG_DIR/gen-${skill_id}.err"); then
+        error "  Claude CLI failed for $skill_id"
+        if [[ $attempt -le $MAX_RETRIES ]]; then
+            warn "  Retrying in ${DELAY}s..."
+            sleep "$DELAY"
+            generate_skill "$category_key" "$skill_id" $((attempt + 1))
+            return $?
+        fi
+        mark_failed "$skill_id" "claude CLI error"
+        return 1
+    fi
+
+    # Write output
+    echo "$output" > "$output_file"
+
+    # Quality gate: check file size
+    local file_size
+    file_size=$(wc -c < "$output_file" | tr -d ' ')
+
+    if [[ $file_size -lt $MIN_SIZE ]]; then
+        warn "  File too small: ${file_size}B (min: ${MIN_SIZE}B)"
+        if [[ $attempt -le $MAX_RETRIES ]]; then
+            warn "  Retrying with stronger prompt..."
+            sleep "$DELAY"
+            generate_skill "$category_key" "$skill_id" $((attempt + 1))
+            return $?
+        fi
+        error "  Giving up on $skill_id (still too small after retries)"
+        mark_failed "$skill_id" "file too small: ${file_size}B"
+        return 1
+    fi
+
+    # Quality gate: check that file starts with # (markdown header)
+    if ! head -1 "$output_file" | grep -q '^# '; then
+        warn "  File doesn't start with markdown header"
+        # Try to fix by removing leading content before first header
+        local temp_file="$output_file.tmp"
+        sed -n '/^# /,$p' "$output_file" > "$temp_file"
+        if [[ -s "$temp_file" ]]; then
+            mv "$temp_file" "$output_file"
+            file_size=$(wc -c < "$output_file" | tr -d ' ')
+        else
+            rm -f "$temp_file"
+        fi
+    fi
+
+    mark_completed "$skill_id" "$file_size"
+    success "  Generated: $skill_id (${file_size}B)"
+
+    # Rate limiting
+    sleep "$DELAY"
+}
+
+# Generate all skills in a category
+generate_category() {
+    local category_key="$1"
+
+    local category_name
+    category_name=$(jq -r --arg key "$category_key" '.categories[$key].name' "$MANIFEST_FILE")
+    local skill_count
+    skill_count=$(jq --arg key "$category_key" '.categories[$key].skills | length' "$MANIFEST_FILE")
+
+    log ""
+    log "═══════════════════════════════════════"
+    log "Category: $category_name ($skill_count skills)"
+    log "═══════════════════════════════════════"
+
+    local skill_ids=()
+    while IFS= read -r line; do
+        skill_ids+=("$line")
+    done < <(jq -r --arg key "$category_key" \
+        '.categories[$key].skills[].id' "$MANIFEST_FILE")
+
+    local generated=0
+    for skill_id in "${skill_ids[@]}"; do
+        if generate_skill "$category_key" "$skill_id"; then
+            generated=$((generated + 1))
+        fi
+
+        # Pilot mode: stop after N skills total
+        if [[ $PILOT -gt 0 ]]; then
+            local total_completed
+            total_completed=$(jq '.stats.total_generated' "$STATE_FILE")
+            if [[ $total_completed -ge $PILOT ]]; then
+                warn "Pilot limit reached ($PILOT skills)"
+                return 0
+            fi
+        fi
+    done
+
+    success "Category complete: $generated/$skill_count generated"
+}
+
+# Print summary
+print_summary() {
+    local total_generated total_failed total_bytes
+    total_generated=$(jq '.stats.total_generated' "$STATE_FILE")
+    total_failed=$(jq '.stats.total_failed' "$STATE_FILE")
+    total_bytes=$(jq '.stats.total_bytes' "$STATE_FILE")
+
+    local total_kb=$((total_bytes / 1024))
+
+    echo ""
+    log "═══════════════════════════════════════"
+    log "          GENERATION SUMMARY           "
+    log "═══════════════════════════════════════"
+    success "Generated: $total_generated files ($total_kb KB)"
+    [[ $total_failed -gt 0 ]] && error "Failed: $total_failed files"
+    log "State: $STATE_FILE"
+    log "Output: $REFS_DIR/"
+    log "═══════════════════════════════════════"
+
+    # List failed skills if any
+    if [[ $total_failed -gt 0 ]]; then
+        echo ""
+        warn "Failed skills:"
+        jq -r '.failed[] | "  - \(.id): \(.reason)"' "$STATE_FILE"
+    fi
+}
+
+# Parse arguments
+parse_args() {
+    local category=""
+    local skill=""
+    local wave=""
+
+    while [[ $# -gt 0 ]]; do
+        case "$1" in
+            --category|-c)
+                category="$2"
+                shift 2
+                ;;
+            --skill|-s)
+                skill="$2"
+                shift 2
+                ;;
+            --wave|-w)
+                wave="$2"
+                shift 2
+                ;;
+            --model|-m)
+                MODEL="$2"
+                shift 2
+                ;;
+            --dry-run)
+                DRY_RUN=true
+                shift
+                ;;
+            --pilot)
+                PILOT="$2"
+                shift 2
+                ;;
+            --delay)
+                DELAY="$2"
+                shift 2
+                ;;
+            --min-size)
+                MIN_SIZE="$2"
+                shift 2
+                ;;
+            --max-retries)
+                MAX_RETRIES="$2"
+                shift 2
+                ;;
+            --reset)
+                rm -f "$STATE_FILE"
+                log "State reset"
+                shift
+                ;;
+            --help|-h)
+                cat <<EOF
+Usage: $0 [OPTIONS]
+
+Options:
+  --category, -c KEY   Generate single category
+  --skill, -s ID       Generate single skill
+  --wave, -w N         Generate wave N (1=HIGH, 2=MEDIUM)
+  --model, -m MODEL    Claude model (default: sonnet)
+  --dry-run            Show what would be generated
+  --pilot N            Generate only first N skills (for testing)
+  --delay N            Seconds between API calls (default: 3)
+  --min-size N         Minimum file size in bytes (default: 5000)
+  --max-retries N      Max retries per skill (default: 2)
+  --reset              Clear state and start fresh
+
+Environment:
+  MODEL=sonnet         Override default model
+  MAX_BUDGET_USD=5     Max dollar amount per run
+  PARALLEL=1           Parallel generation (experimental)
+  DELAY=3              Delay between calls
+
+Examples:
+  $0 --pilot 3                         # Test with 3 skills
+  $0 --category rag-architecture       # Generate one category
+  $0 --wave 1 --model sonnet           # Generate all HIGH priority
+  $0 --dry-run                         # Preview without generating
+  MODEL=haiku $0 --wave 2              # MEDIUM priority with haiku
+EOF
+                exit 0
+                ;;
+            *)
+                error "Unknown option: $1"
+                exit 1
+                ;;
+        esac
+    done
+
+    # Return mode and target
+    if [[ -n "$skill" ]]; then
+        echo "skill:$skill"
+    elif [[ -n "$category" ]]; then
+        echo "category:$category"
+    elif [[ -n "$wave" ]]; then
+        echo "wave:$wave"
+    else
+        echo "all"
+    fi
+}
+
+# Find which category a skill belongs to
+find_skill_category() {
+    local skill_id="$1"
+    jq -r --arg id "$skill_id" '
+        .categories | to_entries[] |
+        select(.value.skills | map(.id) | index($id) != null) |
+        .key
+    ' "$MANIFEST_FILE"
+}
+
+# Main
+main() {
+    check_prereqs
+    init_state
+    mkdir -p "$LOG_DIR"
+
+    local mode
+    mode=$(parse_args "$@")
+
+    log "Skill Generation Pipeline"
+    log "Model: $MODEL | Min size: ${MIN_SIZE}B | Delay: ${DELAY}s"
+    $DRY_RUN && warn "DRY RUN MODE — no files will be generated"
+    [[ $PILOT -gt 0 ]] && warn "PILOT MODE — only $PILOT skills"
+    echo ""
+
+    case "$mode" in
+        skill:*)
+            local skill_id="${mode#skill:}"
+            local category_key
+            category_key=$(find_skill_category "$skill_id")
+            if [[ -z "$category_key" ]]; then
+                error "Skill not found in manifest: $skill_id"
+                exit 1
+            fi
+            generate_skill "$category_key" "$skill_id"
+            ;;
+        category:*)
+            local category_key="${mode#category:}"
+            generate_category "$category_key"
+            ;;
+        wave:*)
+            local wave_num="${mode#wave:}"
+            local categories=()
+            while IFS= read -r line; do
+                categories+=("$line")
+            done < <(jq -r --argjson w "$wave_num" \
+                '.waves[] | select(.wave == $w) | .categories[]' "$CATEGORIES_FILE")
+            for cat in "${categories[@]}"; do
+                generate_category "$cat"
+                if [[ $PILOT -gt 0 ]]; then
+                    local total
+                    total=$(jq '.stats.total_generated' "$STATE_FILE")
+                    [[ $total -ge $PILOT ]] && break
+                fi
+            done
+            ;;
+        all)
+            local all_categories=()
+            while IFS= read -r line; do
+                all_categories+=("$line")
+            done < <(jq -r '.categories | keys[]' "$MANIFEST_FILE")
+            for cat in "${all_categories[@]}"; do
+                generate_category "$cat"
+                if [[ $PILOT -gt 0 ]]; then
+                    local total
+                    total=$(jq '.stats.total_generated' "$STATE_FILE")
+                    [[ $total -ge $PILOT ]] && break
+                fi
+            done
+            ;;
+    esac
+
+    print_summary
+}
+
+main "$@"
--- a/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-agent-orchestration.err
+++ b/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-agent-orchestration.err
--- a/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-ai-security-engineering.err
+++ b/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-ai-security-engineering.err
--- a/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-azure-ai-services.err
+++ b/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-azure-ai-services.err
--- a/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-copilot-extensibility.err
+++ b/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-copilot-extensibility.err
--- a/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-cost-optimization.err
+++ b/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-cost-optimization.err
--- a/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-mlops-genaiops.err
+++ b/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-mlops-genaiops.err
--- a/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-monitoring-observability.err
+++ b/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-monitoring-observability.err
--- a/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-norwegian-public-sector-governance.err
+++ b/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-norwegian-public-sector-governance.err
--- a/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-prompt-engineering.err
+++ b/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-prompt-engineering.err
--- a/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-rag-architecture.err
+++ b/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-rag-architecture.err
--- a/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-responsible-ai.err
+++ b/plugins/ms-ai-architect/scripts/skill-gen/logs/expand-responsible-ai.err
--- a/plugins/ms-ai-architect/scripts/skill-gen/logs/gen-azure-ai-search-setup.err
+++ b/plugins/ms-ai-architect/scripts/skill-gen/logs/gen-azure-ai-search-setup.err
--- a/plugins/ms-ai-architect/scripts/skill-gen/logs/gen-chunking-strategies.err
+++ b/plugins/ms-ai-architect/scripts/skill-gen/logs/gen-chunking-strategies.err
--- a/plugins/ms-ai-architect/scripts/skill-gen/logs/gen-embedding-models-selection.err
+++ b/plugins/ms-ai-architect/scripts/skill-gen/logs/gen-embedding-models-selection.err
--- a/plugins/ms-ai-architect/scripts/skill-gen/logs/gen-rag-core-patterns.err
+++ b/plugins/ms-ai-architect/scripts/skill-gen/logs/gen-rag-core-patterns.err
--- a/plugins/ms-ai-architect/scripts/skill-gen/logs/gen-vector-indexing-techniques.err
+++ b/plugins/ms-ai-architect/scripts/skill-gen/logs/gen-vector-indexing-techniques.err
--- a/plugins/ms-ai-architect/scripts/skill-gen/manifest.json
+++ b/plugins/ms-ai-architect/scripts/skill-gen/manifest.json
--- a/plugins/ms-ai-architect/scripts/skill-gen/prompt-template.md
+++ b/plugins/ms-ai-architect/scripts/skill-gen/prompt-template.md
@ -0,0 +1,102 @@
+# Skill Generation Prompt Template
+
+This template is used by `generate-skills.sh` to produce knowledge reference files for the architect plugin.
+
+## Variables
+
+- `{{SKILL_TITLE}}` — English title (e.g., "Azure AI Vision - Overview and Architecture")
+- `{{SKILL_FILENAME}}` — Kebab-case filename without extension (e.g., "azure-ai-vision-overview")
+- `{{CATEGORY_NAME}}` — Category name (e.g., "Azure AI Services (Foundry Tools)")
+- `{{CATEGORY_DIR}}` — Directory name (e.g., "azure-ai-services")
+- `{{CATEGORY_DESCRIPTION}}` — Category context
+- `{{RELATED_SKILLS}}` — Other skills in same category (for cross-referencing)
+- `{{EXISTING_CONTEXT}}` — Summary of existing reference files that overlap
+
+## Prompt
+
+```
+Du er Cosmo Skyberg, en senior Microsoft AI Solution Architect som skriver kunnskapsreferanser for et Claude Code-plugin. Referansene brukes av en AI-arkitekt persona som hjelper norske organisasjoner (spesielt offentlig sektor) med Microsoft AI-løsninger.
+
+## Oppgave
+
+Skriv en komplett kunnskapsreferanse om: **{{SKILL_TITLE}}**
+
+Denne filen tilhører kategorien **{{CATEGORY_NAME}}**: {{CATEGORY_DESCRIPTION}}
+
+## Format-krav (STRENGT)
+
+Filen MÅ følge dette eksakte formatet:
+
+### Header
+```markdown
+# {{SKILL_TITLE}}
+
+**Last updated:** 2026-02
+**Status:** [GA | Preview | Announced]
+**Category:** {{CATEGORY_NAME}}
+
+---
+```
+
+### Innhold (7-15 KB, alle seksjoner påkrevd)
+
+1. **Introduksjon** (2-3 avsnitt)
+   - Hva er dette? Hvorfor er det viktig for enterprise AI?
+   - Plassering i Microsoft-økosystemet
+   - Norsk prosa, engelske tekniske termer
+
+2. **Kjernekomponenter / Nøkkelegenskaper**
+   - Bruk tabeller for sammenligninger
+   - Bullet points for egenskaper
+   - Kodeeksempler der relevant (korte, illustrative)
+
+3. **Arkitekturmønstre**
+   - 2-3 typiske bruksmønstre med ASCII-diagrammer der det hjelper
+   - Når bruke hvert mønster
+   - Fordeler og ulemper
+
+4. **Beslutningsveiledning**
+   - "Velg X når..." beslutningstabell
+   - Vanlige feil og misforståelser
+   - Røde flagg arkitekten bør se etter
+
+5. **Integrasjon med Microsoft-stakken**
+   - Hvordan dette kobles til andre Azure/M365-tjenester
+   - Typiske integrasjonsmønstre
+
+6. **Offentlig sektor (Norge)**
+   - Spesielle hensyn for norsk offentlig sektor
+   - GDPR, Schrems II, AI Act, Forvaltningsloven
+   - Datasuverenitet og residency
+
+7. **Kostnad og lisensiering**
+   - Prismodell (oversikt, ikke detaljerte tall)
+   - Inkludert i hvilke lisenser
+   - Kostnadsoptimaliseringstips
+
+8. **For arkitekten (Cosmo)**
+   - 5-8 nøkkelspørsmål å stille kunden
+   - Vanlige fallgruver
+   - Anbefalinger per modenhetsnivå (starter/intermediate/advanced)
+
+9. **Kilder og verifisering**
+   - Referanser til Microsoft Learn-artikler
+   - Sist verifisert dato
+   - Konfidensnivå per seksjon (Verified / Baseline / Assumed)
+
+## Regler
+
+1. **Norsk prosa, engelske tekniske termer** — Skriv forklaringer på norsk, behold engelske termer for tjenester, konsepter og API-er
+2. **Tabeller over tekst** — Bruk tabeller for sammenligninger, beslutninger, oversikter
+3. **Konkret over vagt** — Spesifikke tall, konkrete eksempler, navngitte tjenester
+4. **Balansert** — Vis både fordeler og ulemper, ikke bare markedsføringssnakk
+5. **Oppdatert** — Bruk 2025-2026 informasjon, nevn GPT-5, AI Act, Foundry Tools (ny branding)
+6. **Confidence markers** — Merk usikre påstander med (anslått) eller (uverifisert)
+7. **Størrelse** — Mål: 7-15 KB (200-400 linjer). Ikke for kort (overfladisk) eller for langt (bloat)
+8. **Ingen duplikering** — Ikke gjenta informasjon som allerede finnes i: {{EXISTING_CONTEXT}}
+
+## Relaterte skills i samme kategori
+{{RELATED_SKILLS}}
+
+Skriv KUN markdown-innholdet. Ingen innledende forklaring eller avsluttende kommentar.
+```
--- a/plugins/ms-ai-architect/scripts/skill-gen/state.json
+++ b/plugins/ms-ai-architect/scripts/skill-gen/state.json
@ -0,0 +1,227 @@
+{
+  "started": "2026-02-03T15:13:03+01:00",
+  "completed": [
+    "rag-core-patterns",
+    "azure-ai-search-setup",
+    "embedding-models-selection",
+    "vector-indexing-techniques",
+    "chunking-strategies",
+    "hybrid-search-configuration",
+    "semantic-ranker-reranking",
+    "citation-tracking",
+    "rag-evaluation-frameworks",
+    "multi-index-federation",
+    "rag-security-rbac",
+    "rag-caching-optimization",
+    "metadata-management-filtering",
+    "graphrag-knowledge-graphs",
+    "rag-query-understanding",
+    "rag-context-windows",
+    "streaming-rag-responses",
+    "rag-iterative-refinement",
+    "rag-enterprise-scale",
+    "rag-document-preprocessing",
+    "rag-hallucination-mitigation",
+    "rag-cost-optimization",
+    "azure-ai-vision-ocr-processing",
+    "azure-ai-vision-image-analysis",
+    "document-intelligence-prebuilt-models",
+    "document-intelligence-custom-models",
+    "speech-services-speech-to-text",
+    "speech-services-text-to-speech",
+    "speech-services-speaker-recognition",
+    "language-services-text-analytics",
+    "language-services-question-answering",
+    "language-services-custom-text-classification",
+    "translator-document-translation",
+    "translator-custom-neural-models",
+    "content-understanding-multimodal-analysis",
+    "ai-services-networking-security",
+    "ai-services-monitoring-logging",
+    "ai-services-api-best-practices",
+    "ai-services-governance-compliance",
+    "ai-services-cost-optimization",
+    "ai-services-enterprise-architecture",
+    "ai-services-vs-foundry-tools-selection",
+    "responsible-ai-framework-overview",
+    "ai-act-compliance-guide",
+    "bias-detection-mitigation-strategies",
+    "ai-governance-structure-framework",
+    "ai-center-of-excellence-setup",
+    "red-teaming-ai-models",
+    "model-explainability-interpretability",
+    "content-safety-implementation",
+    "ai-impact-assessment-framework",
+    "transparency-documentation-standards",
+    "gdpr-compliance-ai-systems",
+    "algorithmic-accountability-auditability",
+    "fairness-testing-measurement",
+    "ai-ethics-in-public-sector",
+    "model-monitoring-drift-detection",
+    "stakeholder-communication-ai-decisions",
+    "ai-risk-taxonomy-classification",
+    "responsible-ai-policy-development",
+    "data-quality-responsible-ai",
+    "human-in-the-loop-oversight",
+    "responsible-ai-training-awareness",
+    "continuous-improvement-feedback-loops",
+    "declarative-agents-fundamentals",
+    "custom-engine-agents-development",
+    "copilot-studio-topics-and-entities",
+    "microsoft-graph-api-copilot-integration",
+    "copilot-connectors-design-patterns",
+    "mcp-protocol-copilot-studio",
+    "teams-copilot-message-extensions",
+    "sharepoint-copilot-agents",
+    "m365-copilot-plugins-ecosystem",
+    "copilot-orchestration-multi-agent",
+    "copilot-dlp-and-governance",
+    "copilot-analytics-and-usage-insights",
+    "copilot-prompt-engineering-governance",
+    "declarative-agents-grounding-strategies",
+    "copilot-studio-nlp-configuration",
+    "copilot-extensibility-security-patterns",
+    "power-automate-copilot-integration",
+    "copilot-context-window-optimization",
+    "adaptive-cards-copilot-responses",
+    "copilot-api-rate-limiting-resilience",
+    "copilot-studio-localization-globalization",
+    "enterprise-governance-copilot-deployment",
+    "system-message-design-patterns",
+    "few-shot-learning-techniques",
+    "chain-of-thought-prompting",
+    "reasoning-models-o1-o3-optimization",
+    "structured-output-formatting",
+    "function-calling-and-tool-use",
+    "grounding-and-knowledge-injection",
+    "temperature-sampling-and-parameters",
+    "token-optimization-and-efficiency",
+    "prompt-testing-and-evaluation",
+    "adversarial-prompting-and-jailbreaks",
+    "multi-turn-conversation-management",
+    "role-playing-and-persona-techniques",
+    "error-handling-and-fallback-prompting",
+    "domain-specific-prompt-optimization",
+    "multimodal-prompt-design",
+    "real-time-reasoning-performance",
+    "regulatory-and-compliance-prompting",
+    "token-counting-optimization",
+    "semantic-caching-patterns",
+    "reserved-capacity-planning",
+    "model-selection-price-performance",
+    "ptu-vs-paygo-economics",
+    "batch-processing-cost-reduction",
+    "azure-cost-management-ai",
+    "request-batching-aggregation",
+    "prompt-engineering-cost-reduction",
+    "vector-storage-cost-optimization",
+    "ai-builder-credits-transition",
+    "cost-allocation-chargeback",
+    "budget-forecasting-ai-projects",
+    "small-language-models-economics",
+    "rag-query-cost-reduction",
+    "azure-ai-foundry-cost-governance",
+    "multi-model-strategy-costs",
+    "inference-endpoint-cost-optimization",
+    "licensing-compliance-cost-avoidance",
+    "observability-cost-reduction",
+    "mlops-fundamentals-overview",
+    "azure-ml-pipelines-orchestration",
+    "model-versioning-registry-management",
+    "ci-cd-for-ml-models",
+    "contextual-retrieval",
+    "late-chunking-patterns",
+    "hierarchical-rag-patterns",
+    "agentic-rag-patterns",
+    "self-reflective-rag",
+    "multimodal-rag",
+    "model-evaluation-frameworks",
+    "ab-testing-llm-applications",
+    "data-drift-monitoring-detection",
+    "model-drift-performance-degradation",
+    "automated-retraining-pipelines",
+    "prompt-flow-production-deployment",
+    "model-deployment-strategies-azure",
+    "inferencing-optimization-caching",
+    "llm-evaluation-production",
+    "monitoring-observability-ml-systems",
+    "governance-audit-ml-operations",
+    "genaiops-llm-specific-practices",
+    "cost-optimization-mlops-pipelines",
+    "infrastructure-as-code-mlops",
+    "mlops-security-access-control",
+    "feedback-loops-continuous-improvement",
+    "responsible-ai-mlops-integration",
+    "mlops-teams-collaboration-tools",
+    "utredningsinstruksen-ai-methodology",
+    "forvaltningsloven-ai-decisions",
+    "digdir-principle-1-user-centric-design",
+    "digdir-principle-2-interoperability",
+    "digdir-principle-4-trust-security",
+    "digital-samhandling-eif-5-layers",
+    "dpia-norwegian-methodology-ai",
+    "ros-analyse-ai-systems",
+    "nsm-grunnprinsipper-ai-mapping",
+    "anskaffelser-ai-procurement-framework",
+    "gevinstrealisering-ai-projects",
+    "norge-ai-strategy-government",
+    "digdir-ai-governance-structure",
+    "statistical-ethics-ssa-methodology",
+    "public-sector-ai-ethics-framework",
+    "accessibility-requirements-wcag-norway",
+    "copyright-ai-training-data-norway",
+    "budget-and-accounting-ai-costs",
+    "digital-accessibility-action-plan",
+    "citizen-communication-ai-decisions",
+    "prompt-injection-defense-patterns",
+    "jailbreak-prevention-production",
+    "content-safety-filter-calibration",
+    "pii-detection-norwegian-context",
+    "ai-threat-modeling-stride",
+    "ai-security-scoring-framework",
+    "ai-incident-response-procedures",
+    "output-validation-grounding-verification",
+    "zero-trust-ai-services",
+    "data-leakage-prevention-ai",
+    "adversarial-input-robustness-testing",
+    "model-fingerprinting-watermarking",
+    "secure-model-deployment-hardening",
+    "ai-red-team-operations-practical",
+    "supply-chain-security-ai-models",
+    "azure-monitor-setup-ai-workloads",
+    "application-insights-llm-monitoring",
+    "token-usage-tracking-attribution",
+    "anomaly-detection-ai-systems",
+    "custom-dashboards-ai-operations",
+    "log-analytics-kql-ai-queries",
+    "distributed-tracing-ai-pipelines",
+    "sla-monitoring-ai-services",
+    "model-performance-drift-detection",
+    "security-and-audit-logging-ai",
+    "cost-monitoring-cost-attribution",
+    "response-quality-metrics-rag",
+    "endpoint-health-and-capacity-planning",
+    "real-time-streaming-monitoring",
+    "compliance-monitoring-ai-governance",
+    "alerting-strategies-escalation",
+    "observability-for-copilot-extensions",
+    "data-residency-audit-monitoring",
+    "multi-agent-orchestration-patterns",
+    "agent-to-agent-communication",
+    "semantic-kernel-agents-implementation",
+    "agent-memory-and-context-management",
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+    "agent-autonomy-and-control-governance",
+    "agent-365-governance-and-deployment",
+    "agent-evaluation-testing-frameworks",
+    "autonomous-workflow-automation-patterns"
+  ],
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+  "skipped": [],
+  "stats": {
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+    "total_bytes": 4673862
+  }
+}