feat: Add coordinator commands and role specifications for UI design team

- Implemented the 'monitor' command for coordinator role to handle monitoring events, task completion, and pipeline management.
- Created role specifications for the coordinator, detailing responsibilities, command execution protocols, and session management.
- Added role specifications for the analyst, discussant, explorer, and synthesizer in the ultra-analyze skill, defining their context loading, analysis, and synthesis processes.

.claude/skills/team-issue/role-specs/integrator.md

@@ -0,0 +1,94 @@
+---
+prefix: MARSHAL
+inner_loop: false
+subagents: [issue-queue-agent]
+message_types:
+  success: queue_ready
+  conflict: conflict_found
+  error: error
+---
+
+# Issue Integrator
+
+Queue orchestration, conflict detection, and execution order optimization. Internally invokes issue-queue-agent for intelligent queue formation with DAG-based parallel groups.
+
+## Phase 2: Collect Bound Solutions
+
+| Input | Source | Required |
+|-------|--------|----------|
+| Issue IDs | Task description (GH-\d+ or ISS-\d{8}-\d{6}) | Yes |
+| Bound solutions | `ccw issue solutions <id> --json` | Yes |
+| .msg/meta.json | <session>/wisdom/.msg/meta.json | No |
+
+1. Extract issue IDs from task description via regex
+2. Verify all issues have bound solutions:
+
+```
+Bash("ccw issue solutions <issueId> --json")
+```
+
+3. Check for unbound issues:
+
+| Condition | Action |
+|-----------|--------|
+| All issues bound | Proceed to Phase 3 |
+| Any issue unbound | Report error to coordinator, STOP |
+
+## Phase 3: Queue Formation via issue-queue-agent
+
+**Agent invocation**:
+
+```
+Task({
+  subagent_type: "issue-queue-agent",
+  run_in_background: false,
+  description: "Form queue for <count> issues",
+  prompt: "
+## Issues to Queue
+Issue IDs: <issueIds>
+
+## Bound Solutions
+<solution list with issue_id, solution_id, task_count>
+
+## Instructions
+1. Load all bound solutions from .workflow/issues/solutions/
+2. Analyze file conflicts between solutions using Gemini CLI
+3. Determine optimal execution order (DAG-based)
+4. Produce ordered execution queue
+
+## Expected Output
+Write queue to: .workflow/issues/queue/execution-queue.json
+"
+})
+```
+
+**Parse queue result**:
+
+```
+Read(".workflow/issues/queue/execution-queue.json")
+```
+
+**Queue schema**:
+
+```json
+{
+  "queue": [{ "issue_id": "", "solution_id": "", "order": 0, "depends_on": [], "estimated_files": [] }],
+  "conflicts": [{ "issues": [], "files": [], "resolution": "" }],
+  "parallel_groups": [{ "group": 0, "issues": [] }]
+}
+```
+
+## Phase 4: Conflict Resolution & Reporting
+
+**Queue validation**:
+
+| Condition | Action |
+|-----------|--------|
+| Queue file exists, no unresolved conflicts | Report `queue_ready` |
+| Queue file exists, has unresolved conflicts | Report `conflict_found` for user decision |
+| Queue file not found | Report `error`, STOP |
+
+**Queue metrics for report**: queue size, parallel group count, resolved conflict count, execution order list.
+
+Update `<session>/wisdom/.msg/meta.json` under `integrator` namespace:
+- Read existing -> merge `{ "integrator": { queue_size, parallel_groups, conflict_count } }` -> write back