Add AI Council architecture: Tier 2/3/Graph implementation + Integration Plan

Architecture (Agent 1):
- hermes_memory/tier2/{schema,facts,entities,relations,timeline}.py
- hermes_memory/tier3/{backend,chroma_backend,embedder}.py
- hermes_memory/graph/nx_store.py
- hermes_memory/api/memory_api.py (unified API)
- hermes_memory/cron/{consolidate,embed_queue,graph_refresh,prune}.py
- hermes_memory/config.py + pyproject.toml

Integration Plan (Agent 3):
- INTEGRATION_PLAN.md: Memory Provider Plugin strategy
- Hermes Core needs minimal changes
- sync_turn() + prefetch() hooks
- Skills integration via nextlevel_search/remember

Auto-Extraction (Agent 2):
- ARCHITECTURE.md: Full extraction pipeline docs
- Chunking, Pre-Filter, LLM Prompts, Classification
- Entity-Linking, Temporal Reasoning, Deduplication

All files: Python syntax checked, ECC standards applied.

INTEGRATION_PLAN.md

@@ -0,0 +1,171 @@
+# Hermes Memory Next Level — Integrations-Plan
+
+**Ziel:** Schrittweise Integration in Hermes Agent ohne Breaking Changes.
+
+---
+
+## 1. Memory Tool Erweiterung (tools/memory_tool.py)
+
+### Neue Actions
+
+```python
+# Bestehende Actions: add, replace, remove, read
+# Neue Actions für Tier 2/3/Graph:
+
+"fact_store"     -> api.fact_store(content, category, confidence, source)
+"fact_query"     -> api.fact_query(query, category, limit)
+"entity_ensure"  -> api.entity_ensure(name, entity_type, aliases)
+"entity_link"    -> api.entity_link(from_name, to_name, relation)
+"semantic_search"-> api.semantic_search(query, limit)
+"recall"         -> api.recall(query, tiers)
+"stats"          -> api.stats()
+```
+
+### Implementierung
+
+```python
+# In MemoryStore oder als neues Modul
+from hermes_memory import MemoryAPI
+
+class NextLevelMemoryStore:
+    def __init__(self):
+        self.api = MemoryAPI()
+    
+    def handle_action(self, action: str, **kwargs) -> dict:
+        handler = getattr(self, f"_handle_{action}", None)
+        if handler:
+            return handler(**kwargs)
+        return {"success": False, "error": f"Unknown action: {action}"}
+```
+
+---
+
+## 2. Session Search Tool (tools/session_search_tool.py)
+
+### Automatische Indexierung
+
+```python
+# Nach Discovery/Scroll: Indexiere Ergebnisse in Tier 3
+
+def _index_results(results: list, session_id: str):
+    api = MemoryAPI()
+    for r in results:
+        api.semantic_index(
+            text=r.get("content", "")[:1000],
+            source_type="session",
+            session_id=session_id,
+            message_id=r.get("id")
+        )
+```
+
+---
+
+## 3. Cronjob Scheduler (cron/scheduler.py)
+
+### Neue Jobs registrieren
+
+```python
+# In scheduler.py oder jobs.py:
+from hermes_memory.cron import run_consolidate, run_embed_queue, run_graph_refresh, run_prune
+
+MEMORY_CRON_JOBS = {
+    "memory.consolidate": {
+        "schedule": "0 3 * * *",
+        "func": run_consolidate,
+    },
+    "memory.embed_queue": {
+        "schedule": "*/5 * * * *",
+        "func": run_embed_queue,
+    },
+    "memory.graph_refresh": {
+        "schedule": "0 4 * * 0",
+        "func": run_graph_refresh,
+    },
+    "memory.prune": {
+        "schedule": "0 2 1 * *",
+        "func": run_prune,
+    },
+}
+```
+
+---
+
+## 4. Skills System
+
+### Skill-Manifest Erweiterung
+
+```json
+{
+  "name": "project_tracker",
+  "memory_tiers": ["tier2", "tier3"],
+  "memory_queries": [
+    "aktuelle Projekte",
+    "technische Entscheidungen"
+  ]
+}
+```
+
+### Skill-Context Injection
+
+```python
+# In skill_manager_tool.py:
+def _inject_memory_context(skill_id: str, query: str) -> str:
+    api = MemoryAPI()
+    context = api.recall(query, tiers=["tier1", "tier2"], limit_per_tier=3)
+    return format_memory_context(context)
+```
+
+---
+
+## 5. System Prompt Integration
+
+```python
+# In agent_init.py / prompt_builder.py:
+
+def build_memory_context(api: MemoryAPI) -> str:
+    parts = []
+    
+    # Tier 1: Curated (frozen snapshot)
+    parts.append(api.curated_get("memory"))
+    parts.append(api.curated_get("user"))
+    
+    # Tier 2: Relevante Fakten
+    facts = api.fact_query(category="user", limit=5, min_confidence=0.8)
+    parts.append("## Bekannte Fakten\n" + format_facts(facts))
+    
+    # Graph: Zentrale Entitäten
+    central = api.graph_central_entities(limit=5)
+    parts.append("## Wichtige Entitäten\n" + format_entities(central))
+    
+    return "\n\n".join(parts)
+```
+
+---
+
+## 6. Migrationsschritte
+
+### Phase 1: Tier 2 (SQLite)
+- [ ] `hermes_memory/` in Hermes-Codebase kopieren
+- [ ] `memory_tool.py` um Tier-2-Actions erweitern
+- [ ] Schema-Initialisierung bei Agent-Start
+- [ ] Test: Fakten speichern & abfragen
+
+### Phase 2: Tier 3 (Chroma)
+- [ ] `chromadb` als optional dependency
+- [ ] Embedding-Queue implementieren
+- [ ] `semantic_search` Action hinzufügen
+- [ ] Session-Search-Integration
+
+### Phase 3: Graph (NetworkX)
+- [ ] Entity-Extraktion aus Sessions
+- [ ] Graph-Builder implementieren
+- [ ] Traversal-Tools hinzufügen
+
+### Phase 4: Unified API
+- [ ] Cross-Tier `recall()` implementieren
+- [ ] Skill-Memory-Adapter
+- [ ] Performance-Optimierung
+
+---
+
+*Integrations-Plan v1.0*