| name | agentdb-status |
| description | Show AgentDB health — pattern count, embedder status, cache hit rate, learning gain since init. Use when the user asks "is agentdb working?", "how many memories?", "show agentdb stats", or after long-running sessions to confirm state. |
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
- Call
agentdb_pattern_stats to get pattern count, hit rate, recent insert/search latencies.
- If available, call
agentdb_reflexion_stats for episode count and per-task win rates.
- Call
agentdb_bandit_stats (if agentdb-learning is installed) for arm reward summaries.
- 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)
- 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).