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.
2026-07-29 17:07:45 +07:00
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+---
+description: >
+  Analyze workflow patterns using the Agent Monitor's workflow intelligence
+  API — orchestration DAGs, tool flow transitions, subagent effectiveness,
+  model delegation patterns, error propagation by depth, concurrency lanes,
+  compaction impact, and agent co-occurrence. Produces prioritized optimization
+  recommendations with quantified impact.
+---
+
+# Workflow Optimizer
+
+Analyze Claude Code workflows using the Agent Monitor's workflow intelligence engine.
+
+## Input
+
+The user provides: **$ARGUMENTS**
+
+Options: "analyze", a session ID for single-session analysis, or a focus: "tools", "subagents", "cost", "errors".
+
+## Data Sources
+
+| Endpoint | Returns |
+|----------|---------|
+| `GET /api/sessions?limit=100` | Session list with metadata |
+| `GET /api/workflows/{sessionId}` | **11 workflow datasets** (see below) |
+| `GET /api/analytics` | Tool usage top 20, event types, agent types |
+| `GET /api/pricing` | Model pricing rules for cost comparison |
+
+### Workflow Intelligence API (`GET /api/workflows/{sessionId}`)
+
+Returns these 11 datasets per session:
+
+| Dataset | Content |
+|---------|---------|
+| `stats` | Aggregate session stats: tool count, agent depth, event count |
+| `orchestration` | **DAG**: agent nodes with parent/child edges, depths, types |
+| `toolFlow` | **Transition matrix**: tool A → tool B with counts (common sequences) |
+| `effectiveness` | **Subagent success**: per-type completion rates, avg duration, task success |
+| `patterns` | **Recurring sequences**: detected workflow patterns with frequency |
+| `modelDelegation` | **Model choices**: which models are delegated which tasks |
+| `errorPropagation` | **Error flow by depth**: where in the agent tree errors originate and propagate |
+| `concurrency` | **Concurrency lanes**: overlapping agent execution timelines |
+| `complexity` | **Complexity score**: numerical score based on depth, breadth, tool diversity |
+| `compaction` | **Compaction impact**: token savings, frequency, context health |
+| `cooccurrence` | **Agent pairs**: which agents frequently run together |
+
+## Optimization Analyses
+
+### 1. Tool Flow Optimization
+From `toolFlow` transition data:
+- Identify the most common tool sequences (e.g., Read → Edit → Bash)
+- Find redundant transitions (same tool called repeatedly = retries)
+- Detect anti-patterns: high-frequency failure loops
+- Recommend tool chain shortcuts
+
+### 2. Subagent Strategy
+From `effectiveness` + `orchestration`:
+- Which subagent types (task, explore, code-review) have highest completion rates
+- Average duration per subagent type — are subagents taking too long?
+- Underutilized types: tasks that could benefit from delegation
+- Over-spawning: too many subagents for simple tasks
+
+### 3. Model Delegation Analysis
+From `modelDelegation`:
+- Which models handle which task types
+- Cost-per-task comparison across models
+- Opportunities to delegate simple tasks to cheaper models (Haiku/Sonnet instead of Opus)
+- Calculate estimated savings from model rebalancing
+
+### 4. Error Prevention
+From `errorPropagation`:
+- Where errors originate (agent depth level)
+- How errors cascade to parent agents
+- Error types (APIError, tool failure) by frequency
+- Defensive strategies: which patterns lead to fewer errors
+
+### 5. Concurrency Optimization
+From `concurrency`:
+- Which agents run in parallel vs sequential
+- Bottlenecks: sequential agents that could be parallelized
+- Resource contention: overlapping heavy tasks
+
+### 6. Context Health
+From `compaction`:
+- How often compaction occurs per session
+- Token recovery from compaction baselines
+- Sessions that hit context limits — suggest breaking into smaller tasks
+
+## Output
+
+Prioritized recommendations table:
+
+| # | Recommendation | Source Data | Impact | Effort | Est. Savings |
+|---|---------------|-------------|--------|--------|-------------|
+
+Top 5 recommendations with detailed explanation, supporting data from the workflow API, and implementation steps.