Agent Skills: Team UI Design

Team UI Design

Systematic UI design pipeline: research -> design tokens -> review -> implementation. Built on team-worker agent architecture — all worker roles share a single agent definition with role-specific Phase 2-4 loaded from roles/<role>/role.md.

Architecture

Skill(skill="team-uidesign", args="task description")
                    |
         SKILL.md (this file) = Router
                    |
     +--------------+--------------+
     |                             |
  no --role flag              --role <name>
     |                             |
  Coordinator                  Worker
  roles/coordinator/role.md    roles/<name>/role.md
     |
     +-- analyze → dispatch → spawn workers → STOP
                                    |
                    +-------+-------+-------+-------+
                    v       v       v       v
           [team-worker agents, each loads roles/<role>/role.md]
          researcher  designer  reviewer  implementer

Role Registry

Role Router

Parse $ARGUMENTS:

• Has --role <name> → Read roles/<name>/role.md, execute Phase 2-4
• No --role → roles/coordinator/role.md, execute entry router

Delegation Lock

Coordinator is a PURE ORCHESTRATOR. It coordinates, it does NOT do.

Before calling ANY tool, apply this check:

If a tool call is BLOCKED: STOP. Create a task, spawn a worker.

No exceptions for "simple" tasks. Even a single-file read-and-report MUST go through spawn_agent.

Shared Constants

• Session prefix: UDS
• Session path: .workflow/.team/UDS-<date>-<slug>/
• CLI tools: ccw cli --mode analysis (read-only), ccw cli --mode write (modifications)
• Message bus: mcp__ccw-tools__team_msg(session_id=<session-id>, ...)
• Max GC rounds: 2

Worker Spawn Template

Coordinator spawns workers using this template:

spawn_agent({
  agent_type: "team_worker",
  task_name: "<task-id>",
  fork_turns: "none",
  message: `## Role Assignment
role: <role>
role_spec: <skill_root>/roles/<role>/role.md
session: <session-folder>
session_id: <session-id>
requirement: <task-description>
inner_loop: false

Read role_spec file (<skill_root>/roles/<role>/role.md) to load Phase 2-4 domain instructions.

## Task Context
task_id: <task-id>
title: <task-title>
description: <task-description>
pipeline_phase: <pipeline-phase>

## Upstream Context
<prev_context>`
})

After spawning, use wait_agent({ timeout_ms: 1800000 }) to collect results. If result.timed_out, send STATUS_CHECK via followup_task (wait 3 min), then FINALIZE with interrupt (wait 3 min), then mark timed_out and close agents. Use close_agent({ target }) each worker.

Model Selection Guide

UI design is a creative pipeline where research findings inform design decisions. Researcher needs thorough analysis, designer needs creative reasoning.

Research-to-Design Context Flow

Researcher findings must reach designer via coordinator's upstream context:

// After RESEARCH-001 completes, coordinator sends findings to designer
spawn_agent({
  agent_type: "team_worker",
  task_name: "DESIGN-001",
  fork_turns: "none",
  message: `## Upstream Context
Research findings: <session>/research/design-intelligence.json
Component inventory: <session>/research/component-inventory.json
Accessibility audit: <session>/research/accessibility-audit.json`
})

User Commands

Specs Reference

• specs/pipelines.md — Pipeline definitions and task registry

Session Directory

.workflow/.team/UDS-<date>-<slug>/
├── .msg/
│   ├── messages.jsonl         # Team message bus
│   └── meta.json              # Pipeline config + GC state
├── research/                  # Researcher output
│   ├── design-system-analysis.json
│   ├── component-inventory.json
│   ├── accessibility-audit.json
│   └── design-intelligence.json
├── design/                    # Designer output
│   ├── design-tokens.json
│   ├── component-specs/
│   └── layout-specs/
├── audit/                     # Reviewer output
│   └── audit-*.md
├── build/                     # Implementer output
│   ├── token-files/
│   └── component-files/
└── wisdom/                    # Cross-task knowledge

v4 Agent Coordination

Message Semantics

Agent Health Check

Use list_agents({}) in handleResume and handleComplete:

// Reconcile session state with actual running agents
const running = list_agents({})
// Compare with meta.json active tasks
// Reset orphaned tasks (in_progress but agent gone) to pending

Named Agent Targeting

Workers are spawned with task_name: "<task-id>" enabling direct addressing:

• send_message({ target: "DESIGN-001", message: "..." }) -- send additional research findings to designer
• followup_task({ target: "BUILD-001", message: "..." }) -- assign implementation from reviewed design specs
• close_agent({ target: "AUDIT-001" }) -- cleanup after design audit

Error Handling