feat: Claude Code Monitor — lanes, pipelines and a merged workspace

Internal SmartGift build of a Claude Code monitoring dashboard.

Lanes: a durable unit of parallel agent work, one per working directory,
tracked across session restarts. Managed lanes are git worktrees the
dashboard provisions and can reset or remove behind a three-check destroy
guard and a counted preflight; adopted lanes are directories you already
own and are never destroyable.

Pipelines: a lane moves through pipeline stages. A stage the agent declares
with evidence renders green; a stage inferred from the tool-event stream
renders dashed amber and never counts as done. Detection is forward-only
within a 30-minute window, and never writes the declared stage.

Workspace: one page at /run with a lane grid, the selected lane's pipeline,
and a full Claude console behind a disclosure.

plugins/ccam-insights/skills/anomaly-alert/SKILL.md

@@ -0,0 +1,88 @@
+---
+description: >
+  Identify anomalous sessions using Agent Monitor data — cost outliers from
+  the pricing engine, token anomalies (cache miss spikes, compaction baseline
+  surges), unusual event type ratios (PreToolUse/PostToolUse gaps, APIError
+  clusters), behavioral deviations from workflow intelligence (complexity
+  score outliers, error propagation anomalies), and sessions with abnormal
+  metadata (extreme turn_count, high thinking_blocks, zero turn_duration).
+---
+
+# Anomaly Alert
+
+Detect anomalous sessions in Claude Code Agent Monitor data.
+
+## Input
+
+The user provides: **$ARGUMENTS**
+
+This may be:
+- "all" or empty (default: check all anomaly types)
+- "cost" for cost anomalies only
+- "duration" for duration anomalies only
+- "errors" for error rate anomalies only
+- A sensitivity level: "strict" (1σ), "normal" (2σ), "relaxed" (3σ)
+
+## Procedure
+
+1. **Fetch baseline data** from `http://localhost:4820`:
+   - `GET /api/sessions?limit=500` — historical sessions for baseline
+   - `GET /api/analytics` — aggregated metrics
+   - `GET /api/pricing/cost` — cost data per session
+
+2. **Compute baselines** for each metric:
+   - Mean, median, standard deviation
+   - P25, P75, P90, P95, P99 percentiles
+   - Interquartile range (IQR) for robust outlier detection
+
+3. **Detect anomalies** using statistical thresholds:
+
+   ### Cost Anomalies
+   - Sessions costing >2σ above mean
+   - Single sessions exceeding daily average
+   - Sudden cost spikes (session-over-session increase >200%)
+
+   ### Duration Anomalies
+   - Sessions lasting >2σ above mean duration
+   - Extremely short sessions (<1 minute) that still incur cost
+   - Sessions with unusual active-vs-idle ratios
+
+   ### Error Rate Anomalies
+   - Sessions with error rates >2σ above baseline
+   - New error types not seen in previous sessions
+   - Sessions with >3 consecutive tool failures
+
+   ### Behavioral Anomalies
+   - Unusual tool combinations not seen before
+   - Sessions with abnormally high compaction counts
+   - Model switches mid-session (if unexpected)
+   - Sessions with no tool usage (pure conversation)
+
+   ### Token Anomalies
+   - Input/output token ratio far from historical norm
+   - Cache miss rate significantly higher than average
+   - Token usage growing faster than session count
+
+4. **Classify each anomaly**:
+   - **🔴 Critical**: Likely indicates a real problem requiring attention
+   - **🟡 Warning**: Unusual but may be expected for certain tasks
+   - **🔵 Info**: Interesting deviation worth noting
+
+## Output Format
+
+Present as an **Anomaly Report**:
+
+```
+═══════════════════════════════════════════════
+  ANOMALY DETECTION REPORT
+  Analyzed: N sessions | Baseline: last 30 days
+  Anomalies found: N (🔴 N critical, 🟡 N warn, 🔵 N info)
+═══════════════════════════════════════════════
+```
+
+For each anomaly:
+- Session ID and timestamp
+- Anomaly type and severity
+- Observed value vs expected range
+- Possible explanation
+- Recommended action (if any)