feat(ops): make hierarchy depth configurable and finalize recursive O'Reilly architecture documentation

README.md

@@ -269,7 +269,7 @@ To embrace the diverse global Cloud Native community while maintaining internati
     *   `complexity`: Target audience level (e.g., 'Beginner', 'Architect').
     *   `author`: Technical creator/contributor identification.
     *   `duration` / `reading_time`: Automatic extraction of content length for videos and articles.
-    *   `area` / `topic` / `subtopic`: Persistent architectural classification for hierarchical grouping.
+    *   `hierarchy`: Persistent, **recursive technical classification** (list of up to 10 levels) for O'Reilly-style grouping.
 - **Separation of Concerns (Data vs. UI)**:
     *   **The Database (Source of Truth)**: Holds raw data, enabling future features like language-based filtering or statistics without re-processing links.
     *   **The Portal (Visual Rendering)**: The `V2VisionEngine` dynamically converts the `language`, `complexity`, and `type` metadata into visual UI tags (e.g., `[SPANISH CONTENT]`, `[ARCHITECT LEVEL]`) during the site build process.
@@ -438,7 +438,7 @@ graph TD
 
 ### 7.6. Strategic Benefits
 - **Technical Immutability (V1)**: AI agents are strictly forbidden from overwriting human-curated titles, manual 🌟 stars, or additional descriptive comments in the V1 archive, ensuring the bot respects and preserves manual engineering effort.
-- **Structural Intelligence Persistence**: High-precision architectural classification (Area, Topic, Subtopic) is stored as persistent metadata. This allows all workflows to reuse structural insights, reducing AI costs by >90% and ensuring perfect consistency between V1 reorganization and V2 portal generation.
+- **Structural Intelligence Persistence**: High-precision technical classification is stored as a persistent, **recursive hierarchy** (up to 10 levels deep). This allows all workflows to reuse deep structural insights, reducing AI costs by >90% and ensuring perfect consistency between V1 reorganization and V2 portal generation.
 - **Self-Healing Infrastructure**: The engine automatically detects and rescues broken links (e.g., GitHub `master` -> `main` branch migration) and identifies parked/expired domains that bypass standard health checks.
 - **Zero-to-Hero Learning Paths**: V2 resources are systematically grouped by complexity level (Fundamentals, Intermediate, Advanced, Architect), transforming the portal into a structured educational journey for Cloud Native engineering.
 - **Special Assets Preservation**: High-value documents (Introduction, YAML, Awesome repos) undergo high-precision semantic grouping in V1 and exhaustive inclusion in V2 to ensure 100% technical preservation.
@@ -681,7 +681,7 @@ Certain files are designated as **Special Assets** (defined in [`data/special_as
 - **Awesome Repositories**: Preserved curation lists that act as gateways to specialized sub-ecosystems.
 
 **Rules of Engagement:**
-1. **High-Precision Grouping**: AI agents use nested hierarchies (Areas -> Topics -> Subtopics) to organize these files without losing any technically valid reference, following a **Professional Technical Book** (O'Reilly style) structure.
+1. **High-Precision Grouping**: AI agents use **recursive nested hierarchies** (up to 10 levels) to organize these files without losing any technically valid reference, following a **Professional Technical Book** (O'Reilly style) structure.
 2. **Elite Curation**: For the V2 Portal, `introduction.md` undergoes a specialized "Elite selection" (Impact ≥ 4) to ensure a high-density entry point for global users.
 
 ### 🎓 O'Reilly-style Knowledge Architecture

src/v2_optimizer.py

@@ -19,6 +19,8 @@ class V2VisionEngine:
     def __init__(self):
         # Load Special Assets & Rules
         self.special_assets_rules = self._load_special_assets()
+        self.link_rules = self._load_link_rules()
+        self.max_depth = self.link_rules.get("hierarchy_rules", {}).get("max_depth", 10)
         
         # 100% Comprehensive 2026 Taxonomy
         self.dimensions = {
@@ -41,7 +43,7 @@ class V2VisionEngine:
             "PHASE 1: TECHNICAL PRESERVATION & CURATION\n"
             "- KEEP >90% of technical resources (except for 'introduction.md' where only high-impact links are kept).\n"
             "PHASE 2: SOPHISTICATED HIERARCHICAL CLASSIFICATION\n"
-            "- Identify TECHNICAL_HIERARCHY: A list of strings (max 10) representing Area > Topic > Subtopics.\n"
+            "- Identify TECHNICAL_HIERARCHY: A list of strings (max depth configured) representing Area > Topic > Subtopics.\n"
             "- For 'introduction.md', set is_microservice: true if context matches.\n"
             "PHASE 3: KNOWLEDGE ASSIMILATION FLOW\n"
             "- Order hierarchy to facilitate a structured learning journey: from foundations to advanced internals.\n"
@@ -60,6 +62,14 @@ class V2VisionEngine:
             except: return {}
         return {}
 
+    def _load_link_rules(self) -> Dict:
+        path = "data/link_rules.yaml"
+        if os.path.exists(path):
+            try:
+                with open(path, "r") as f: return yaml.safe_load(f) or {}
+            except: return {}
+        return {}
+
     def _load_inventory(self) -> Dict:
         if os.path.exists(INVENTORY_PATH):
             try:
@@ -221,7 +231,7 @@ class V2VisionEngine:
             hierarchy = item.get("hierarchy", [])
             if hierarchy and (hierarchy[0] == dim or hierarchy[0] == cat_name): hierarchy = hierarchy[1:]
             current = v2_structure[dim]["categories"][cat_name]
-            for h_name in hierarchy[:10]:
+            for h_name in hierarchy[:self.max_depth]:
                 if h_name not in current: current[h_name] = {"__links__": []}
                 current = current[h_name]
             current["__links__"].append(item)