agentdb-status

# AgentDB Status Reports the live state of the AgentDB Cognitive Container backing this session. ## When to use - User asks "what's in agentdb?", "is the memory working?", "show stats" - Debugging recall quality — high miss rate? cache cold? - Before / after a long session to see how much was learned - CI smoke check before deploying an agent that depends on AgentDB ## Steps 1. Call `agentdb_pattern_stats` to get pattern count, hit rate, recent insert/search latencies. 2. If available, call `agentdb_reflexion_stats` for episode count and per-task win rates. 3. Call `agentdb_bandit_stats` (if `agentdb-learning` is installed) for arm reward summaries. 4. Render a compact table: ``` patterns 12,847 episodes 384 skills 22 hit rate 94.2% avg search 0.83 ms learning gain +18% since init storage 38 MB (.rvf) ``` 5. If any number looks off (zero patterns, hit rate <50%, latency >10ms), flag it and link to the relevant ADR / docs. ## Don't - Don't dump the raw stats JSON — readers want the summary. - Don't infer "broken" from a fresh init (zero patterns is correct on day 0).