qavr-status

# QAVR Status Diagnostic **Purpose**: Quick diagnostic view of the QAVR learned memory system. ## Usage ``` /qavr-status [context] ``` **Arguments**: - `context` (optional): Specific context to check (e.g., "debugging", "research"). Defaults to showing all contexts. ## What It Shows ### 1. System Status - **Mode**: Cold (< 100 interactions) or Warm (Q-value ranking active) - **Total Memories**: Number of memories with Q-values - **Total Contexts**: Number of distinct context types ### 2. Per-Context Status For each context (or specified context): - Interaction count - Mode (cold/warm) - Interactions remaining until warm ### 3. Top Memories Top 5 memories by Q-value for each warm context: - Memory ID - Q-value - Visit count ### 4. Configuration Current QAVR settings from `~/.claude/qavr/config.yaml` ## Implementation When this skill is invoked, execute the following: ```python import sys sys.path.insert(0, '/home/kim/.claude/qavr') from q_value_store import QValueStore store = QValueStore('/home/kim/.claude/qavr/q_values.json') stats = store.get_stats() print("=" * 50) print("QAVR System Status") print("=" * 50) print(f"Memories tracked: {stats['memory_count']}") print(f"Contexts: {stats['context_count']}") print(f"Warm contexts: {', '.join(stats['warm_contexts']) or 'None'}") print(f"Cold contexts: {', '.join(stats['cold_contexts']) or 'None'}") print(f"Total interactions: {stats['total_interactions']}") print() # Per-context details for ctx in store.context_interactions: mode = store.get_mode(ctx) interactions = store.context_interactions[ctx] remaining = store.interactions_to_warm(ctx) print(f"Context: {ctx}") print(f" Mode: {mode}") print(f" Interactions: {interactions}") if mode == 'cold': print(f" To warm: {remaining} more interactions") else: print(f" Top memories:") for mem in store.get_top_memories(ctx, 5): print(f" {mem['memory_id']}: Q={mem['q']:.3f} ({mem['visits']} visits)") print() # Config summary print("Configuration:") print(f" Learning rate: {store.config.learning_rate}") print(f" Cold threshold: {store.config.cold_start_threshold}") print(f" Min Q threshold: {store.config.min_q_threshold}") ``` ## Example Output ``` ================================================== QAVR System Status ================================================== Memories tracked: 42 Contexts: 3 Warm contexts: debugging, research Cold contexts: implementation Total interactions: 287 Context: debugging Mode: warm Interactions: 156 Top memories: seed_debug_001: Q=0.997 (76 visits) mem_debug_042: Q=0.891 (23 visits) mem_debug_018: Q=0.834 (41 visits) seed_explore_001: Q=0.812 (19 visits) mem_debug_033: Q=0.756 (12 visits) Context: research Mode: warm Interactions: 112 Top memories: mem_research_007: Q=0.923 (34 visits) mem_research_012: Q=0.867 (28 visits) seed_research_001: Q=0.801 (19 visits) Context: implementation Mode: cold Interactions: 19 To warm: 81 more interactions Configuration: Learning rate: 0.1 Cold threshold: 100 Min Q threshold: 0.3 ``` ## Related Skills - `confidence-check-skills` - Pre-implementation validation (uses QAVR for duplicate detection) - `agent-memory-skills` - Agent memory framework with QAVR integration - `chromadb-integration-skills` - ChromaDB patterns (QAVR wraps these)