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: >
+  Generate a daily standup summary from recent Claude Code sessions — completed
+  work grouped by project (cwd), session costs from the pricing engine,
+  tool invocations, error/compaction/APIError events, and turn velocity
+  metrics from session metadata (turn_count, total_turn_duration_ms).
+---
+
+# Daily Standup
+
+Generate a daily standup report from Claude Code Agent Monitor data.
+
+## Input
+
+The user provides: **$ARGUMENTS**
+
+This may be:
+- "today" or empty (default: last 24 hours)
+- "yesterday" for the previous day
+- A specific date: "2025-04-10"
+
+## Procedure
+
+1. **Fetch recent session data** from `http://localhost:4820`:
+   - `GET /api/sessions?limit=50` (default sort: most recently updated first)
+   - Filter sessions that started within the target day
+   - For each matching session: `GET /api/events?session_id={session_id}`
+
+2. **Compile standup sections**:
+
+   ### ✅ What I accomplished
+   - List each completed session with:
+     - Brief description (from session name or first tool's context)
+     - Working directory (project context)
+     - Key tools used and outcomes
+     - Duration and model used
+   - Group by project/working directory if multiple
+
+   ### ⚠️ Issues encountered
+   - Sessions that ended in `error` or `abandoned` status
+   - Tools that failed (from error events)
+   - Compaction events (hit context limits)
+   - Unusually long sessions (>2x average duration)
+
+   ### 📋 Key metrics
+   - Total sessions: N
+   - Total time spent: X hours Y minutes
+   - Tools invoked: N (top 3 listed)
+   - Estimated cost: $X.XX
+   - Completion rate: N%
+
+   ### 🔮 Suggested focus areas
+   - Based on incomplete/error sessions, suggest what to revisit
+   - Based on tool patterns, suggest workflow improvements
+
+3. **Format for standup**:
+   - Keep it concise — aim for a 2-minute read
+   - Lead with accomplishments
+   - Be honest about blockers
+   - Make metrics scannable
+
+## Output Format
+
+Present as a clean standup report with emoji section headers, bullet points for items, and a compact metrics table. Add a one-line summary at the top suitable for pasting into Slack or a team channel.
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+---
+description: >
+  Compile a month-over-month retrospective from Agent Monitor data — sessions,
+  cost, token volumes, completion rate, top projects by working directory, and
+  notable shifts versus the prior month. Uses daily_sessions/daily_events (365d)
+  from analytics, the session list, and the pricing cost breakdown. Use when
+  doing a monthly retrospective or planning the month ahead.
+---
+
+# Monthly Review
+
+Generate a month-over-month productivity retrospective from Agent Monitor data.
+
+## Input
+
+The user provides: **$ARGUMENTS**
+
+This may be:
+- "this month" or empty (default: the current calendar month to date)
+- "last month" for the previous full calendar month
+- A specific month: "2026-02" or "February 2026"
+
+The comparison period is always the immediately preceding calendar month.
+
+## Data Sources
+
+| Endpoint | Returns |
+|----------|---------|
+| `GET /api/analytics` | `daily_sessions` and `daily_events` (365d) for monthly bucketing and trends; `tokens` (total_input/output/cache_read/cache_write — baselines pre-summed); `tool_usage` (top 20); `sessions_by_status` |
+| `GET /api/sessions?limit=500` | Sessions with `started_at`, `ended_at`, `status`, `model`, `cwd`, `cost`, and `metadata` (turn_count, thinking_blocks) — for per-project (cwd) grouping and completion rate |
+| `GET /api/pricing/cost` | `total_cost` and per-model `breakdown` (input/output/cache tokens, cost, matched_rule) |
+
+## Report Sections
+
+### 1. Month at a Glance
+Compare the target month to the prior month in a table:
+
+| Metric | This Month | Last Month | Change |
+|--------|-----------|------------|--------|
+| Sessions | N | N | ▲/▼ N% |
+| Total Cost | $X.XXXX | $X.XXXX | ▲/▼ N% |
+| Tokens (in/out/cache) | N | N | ▲/▼ N% |
+| Completion Rate | N% | N% | ▲/▼ N pts |
+| Active Days | N | N | ▲/▼ |
+
+Derive monthly buckets from `daily_sessions` / `daily_events`. Completion rate =
+`completed sessions / total sessions` for the month (from `sessions_by_status` and
+the filtered session list).
+
+### 2. Top Projects (by cwd)
+Group the month's sessions by `cwd`. For the top 5–8 projects, list session count,
+total cost, completion rate, and dominant model. Note any project that newly
+appeared or dropped off versus last month.
+
+### 3. Cost & Token Breakdown
+From `/api/pricing/cost`, show cost per model and the dominant token type. Compute
+cache hit rate = `total_cache_read / (total_cache_read + total_input)` and compare
+to last month. Currency to 4 decimals.
+
+### 4. Tool & Workflow Shifts
+From `tool_usage`, highlight the tools that rose or fell most month-over-month, and
+any new tool adopted. Flag rising error/Compaction activity if present.
+
+### 5. Notable Shifts & Narrative
+Three to five plain-language observations: what changed, why it likely changed, and
+what it implies (e.g., "cost up 22% but sessions flat → heavier per-session work").
+
+### 6. Focus for Next Month
+Two to four prioritized, actionable goals grounded in the numbers above.
+
+## Output
+
+- Markdown report with emoji-light, scannable section headers.
+- Tables for all month-over-month comparisons; ▲ / ▼ for deltas.
+- Currency in USD to 4 decimals; tokens with thousands separators.
+- Lead with a 2–3 sentence executive summary, then the sections in order.
+- Cite only numbers returned by the API; if a month has no data, say so explicitly.
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+---
+description: >
+  Summarize a sprint's worth of Claude Code activity — sessions grouped by
+  project (cwd), per-model cost breakdown, token efficiency (cache hit rate,
+  compaction baselines), subagent effectiveness from workflow API, velocity
+  metrics (turn_count, turn_duration_ms), and tool diversity across the sprint.
+---
+
+# Sprint Summary
+
+Generate a sprint summary from Claude Code Agent Monitor data.
+
+## Input
+
+The user provides: **$ARGUMENTS**
+
+This may be:
+- A sprint duration: "last 2 weeks", "last 10 days"
+- A date range: "2025-03-31 to 2025-04-13"
+- "current sprint" (default: last 14 days)
+
+## Procedure
+
+1. **Fetch sprint data** from `http://localhost:4820`:
+   - `GET /api/sessions?limit=500` — all sessions in range (default sort: most recently updated first)
+   - `GET /api/analytics` — aggregated metrics
+   - `GET /api/pricing/cost` — total costs
+   - For high-value sessions: `GET /api/events?session_id={id}` — event details
+
+2. **Compile sprint summary**:
+
+   ### 🎯 Sprint Overview
+   - Sprint period: [start] to [end]
+   - Total sessions: N (completed: N, errored: N, abandoned: N)
+   - Total development hours with Claude Code: N
+   - Total cost: $X.XX
+   - Overall completion rate: N%
+
+   ### 📦 Deliverables
+   Group sessions by working directory (project):
+   - **Project A** (`/path/to/project`)
+     - N sessions, N hours, key activities
+   - **Project B** (`/path/to/other`)
+     - N sessions, N hours, key activities
+
+   ### 📊 Velocity Metrics
+   | Metric | Sprint | Previous Sprint | Trend |
+   |--------|--------|-----------------|-------|
+   | Sessions/day | N | N | ↑/↓ |
+   | Avg session duration | Nm | Nm | ↑/↓ |
+   | Cost/session | $N | $N | ↑/↓ |
+   | Tokens/session | N | N | ↑/↓ |
+   | Completion rate | N% | N% | ↑/↓ |
+
+   ### 🛠 Technology Breakdown
+   - Models used with distribution percentages
+   - Top 15 tools by usage with category grouping
+   - Subagent utilization rate
+
+   ### ⚡ Efficiency Analysis
+   - Token efficiency: cache hit rate, compaction frequency
+   - Cost per completed task
+   - Time-to-first-output (avg across sessions)
+   - Error recovery rate (sessions that recovered from errors)
+
+   ### 🔄 Retrospective Data Points
+   - **What went well**: Highest-efficiency sessions, best completion rates
+   - **What could improve**: Most expensive sessions, highest error rates
+   - **Action items**: Data-driven suggestions for next sprint
+
+## Output Format
+
+Professional sprint report suitable for sharing with team leads or managers:
+- Executive summary paragraph (5 sentences max)
+- Structured data tables with trend indicators
+- Grouped deliverables by project
+- Numbered action items at the end
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+---
+description: >
+  Discover when you are most active and most productive with Claude Code by
+  bucketing sessions and events into hour-of-day and day-of-week bins from their
+  timestamps, then flagging peak versus low-output windows. Uses the session
+  list, per-session events, and analytics daily trends. Use when planning a
+  schedule or deciding when to do deep work versus lighter tasks.
+---
+
+# Time of Day
+
+Profile activity and productivity across the hours of the day and days of the week.
+
+## Input
+
+The user provides: **$ARGUMENTS**
+
+This may be:
+- empty or "all" (default: all available sessions)
+- a window like "last 30 days" or "last 90 days" to limit the analysis
+- a project path to scope the analysis to one `cwd`
+
+## Data Sources
+
+| Endpoint | Returns |
+|----------|---------|
+| `GET /api/sessions?limit=500` | Sessions with `started_at`, `ended_at`, `status`, `cwd`, `cost`, and `metadata` (turn_count, total_turn_duration_ms) — primary source for hour/weekday bucketing |
+| `GET /api/events?session_id=X` | Events with `timestamp` and `event_type` (PreToolUse, PostToolUse, Stop, Compaction, APIError, etc.) — finer-grained activity within sessions and error timing |
+| `GET /api/analytics` | `daily_sessions` / `daily_events` (365d) and `sessions_by_status` for trend context and completion baselines |
+
+## Report Sections
+
+### 1. Activity by Hour of Day
+Bucket sessions (by `started_at`) and events (by `timestamp`) into 24 hourly bins.
+Show a text bar chart of session and event counts per hour. Identify the busiest
+hours by raw volume.
+
+### 2. Productivity by Hour of Day
+For each hour bin, compute completion rate (`completed / total` sessions started in
+that hour) and average sustained turn time
+(`total_turn_duration_ms / turn_count`, ms → minutes). Distinguish "active" hours
+(high volume) from "productive" hours (high completion + sustained turns).
+
+### 3. Day-of-Week Pattern
+Bucket the same metrics into 7 weekday bins. Table: weekday, sessions, completion
+rate, avg cost, dominant model.
+
+### 4. Peak vs. Low-Output Windows
+- **Peak windows:** hours/days with high completion rate and long sustained turns.
+- **Low-output windows:** hours/days with high abandonment/error/Compaction rates
+  or fragmented short turns. Pull error timing from `/api/events` event types
+  (APIError, Compaction) to corroborate.
+
+### 5. Schedule Recommendation
+Suggest which hour/weekday blocks to reserve for deep work and which to use for
+lighter or shallower tasks, grounded in the buckets above.
+
+## Output
+
+- Markdown with text-based bar charts (e.g., `09:00 ████████ 24`) for the hourly
+  and weekday distributions.
+- Tables for the hour and weekday metrics; ▲ / ▼ for above/below the overall mean.
+- Currency in USD to 4 decimals; durations in minutes (convert from ms).
+- Cite only numbers from the API. State how many sessions/events were bucketed and
+  exclude sessions missing `started_at` or the focus metadata, noting the count.
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+---
+description: >
+  Compile a weekly productivity report using Agent Monitor data — daily_sessions
+  and daily_events trends, per-session costs from pricing engine, token volumes
+  (input/output/cache_read/cache_write + baselines), tool usage top 20,
+  session completion rates by status, and workflow intelligence metrics.
+---
+
+# Weekly Report
+
+Generate a comprehensive weekly productivity report from Agent Monitor data.
+
+## Input
+
+The user provides: **$ARGUMENTS**
+
+This may be:
+- "this week" or empty (default: current week Mon-Sun)
+- "last week" for the previous week
+- A date range: "2025-04-07 to 2025-04-13"
+
+## Procedure
+
+1. **Fetch weekly data** from `http://localhost:4820`:
+   - `GET /api/sessions?limit=200` — filter to target week (default sort: most recently updated first)
+   - `GET /api/analytics` — aggregated analytics
+   - `GET /api/pricing/cost` — cost data
+
+2. **Build the weekly report**:
+
+   ### 📊 Week at a Glance
+   | Metric | This Week | Last Week | Change |
+   |--------|-----------|-----------|--------|
+   | Sessions | N | N | ↑/↓ N% |
+   | Total Hours | N | N | ↑/↓ N% |
+   | Tokens Used | N | N | ↑/↓ N% |
+   | Total Cost | $X.XX | $X.XX | ↑/↓ N% |
+   | Completion Rate | N% | N% | ↑/↓ |
+
+   ### 🏆 Highlights
+   - Most productive day (by sessions completed)
+   - Longest session and what it accomplished
+   - Most used tools and any new tools adopted
+   - Notable achievements (complex tasks completed, errors resolved)
+
+   ### 📈 Daily Breakdown
+   | Day | Sessions | Hours | Cost | Completion |
+   |-----|----------|-------|------|------------|
+   For each day of the week with activity.
+
+   ### 🔧 Tool Usage Report
+   - Top 10 tools by invocation count
+   - Tools with highest error rate
+   - Tool usage distribution chart (text-based)
+
+   ### 💡 Productivity Insights
+   - Peak productivity hours
+   - Average session duration and trend
+   - Cost efficiency trend
+   - Model usage distribution
+
+   ### 🎯 Recommendations for Next Week
+   - Based on error patterns: what to improve
+   - Based on cost trends: optimization opportunities
+   - Based on tool usage: workflow suggestions
+
+## Output Format
+
+Professional report format with:
+- Executive summary (3 sentences max)
+- Structured tables with week-over-week comparisons
+- Emoji-prefixed section headers for scannability
+- Actionable recommendations in priority order
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+---
+description: >
+  Analyze workflow patterns using the Agent Monitor's workflow intelligence
+  API — orchestration DAGs, tool flow transitions, subagent effectiveness,
+  model delegation patterns, error propagation by depth, concurrency lanes,
+  compaction impact, and agent co-occurrence. Produces prioritized optimization
+  recommendations with quantified impact.
+---
+
+# Workflow Optimizer
+
+Analyze Claude Code workflows using the Agent Monitor's workflow intelligence engine.
+
+## Input
+
+The user provides: **$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.