| name | agent-pipeline |
| description | Multi-Agent Collaborative Pipeline for Claude Code — orchestrates 7 development phases with 6 specialized AI roles |
| version | 2.0.0 |
| author | JS-mark |
| tags | ["multi-agent","pipeline","mcp","development-workflow","automation"] |
/agent — Multi-Agent Collaborative Pipeline
Unified command for the multi-agent development workflow. Dispatches by subcommand.
Usage: /agent <subcommand> [args]
IMPORTANT: All MCP tool calls MUST include the root parameter set to the current working directory (project root). This ensures pipeline data stays per-project, not global.
| Subcommand | Alias | Description |
|---|
run <feature> [phase] | r | Run the 7-phase pipeline |
status | s | Show pipeline progress |
dashboard [port] | d | Start monitoring web UI |
init | i | Initialize workflow in current project |
(no args / help) | h | Show usage guide |
Subcommand: help (default when no args)
Display:
/agent — Multi-Agent Collaborative Pipeline
Usage: /agent <subcommand> [args]
Subcommands:
run <feature> [phase] Run 7-phase pipeline (parallel Phase 2, fix-test loop)
status Show pipeline progress
dashboard [port] Start monitoring dashboard (default port: 3210)
init Initialize multi-agent workflow in current project
Pipeline Phases:
1. PM → PRD 需求文档
2. 并行设计 → 架构师 + UI 设计师 + 测试计划 (并行)
3. 全栈开发 → 代码实现
4. 代码审查 → 审查报告
5. 审查修复 → 修复 Blocker
6. ��试执行 → 编写测试并执行
7. 修复循环 → Bug 修复 + 重新测试 (max 5 rounds)
Quick Start:
/agent init # Initialize (interactive)
/agent run my-feature # Full pipeline
/agent run my-feature 3 # Resume from Phase 3
/agent status # Check progress
/agent dashboard # Visual monitoring
CLI (any project dir):
npx @aspect-mark/agent-pipeline status
npx @aspect-mark/agent-pipeline dashboard [port]
# Or via project shim:
node scripts/pipeline.js status
Subcommand: run
Parse from $ARGUMENTS: skip first word ("run"/"r"), next word = feature name, optional next = start phase 1-7.
Step 0: Validate
- If no feature name, ask the user
- Use MCP tool
pipeline_check_ready with root = current working directory to verify role files exist. If missing, tell user to run /agent init
- Set:
FEATURE, START_PHASE (default 1)
Step 1: Initialize status
Use MCP tool pipeline_init_status with parameters:
root: current working directoryfeature: the feature namestartPhase: the start phase (default 1)maxFixRounds: 5
This creates docs/.pipeline-status.json with the v2 schema.
Step 2: Confirm
Show plan to user and ask for confirmation.
Step 3: Execute phases
Before each phase: use pipeline_update_phase with root = current working directory → status "running"
After each phase: use pipeline_update_phase with root = current working directory → status "done"
Phase 1: PM Agent
Launch one Agent (foreground):
Prompt: "你是产品经理。请阅读 .claude/roles/pm.md 了解你的角色职责和文档模板。
分析功能「<FEATURE>」的需求，编写 PRD 文档并输出到 docs/prd/feature-<FEATURE>.md。
请严格按照角色文件中的 PRD 模板格式编写，包含完整的功能需求、用户故事、验收标准等。"
Phase 2: Parallel Design (3 Agents)
CRITICAL: Launch all 3 Agent tool calls in a SINGLE message for parallel execution:
Before launching: use pipeline_update_phase phaseId=2, status="running"
Agent 2a - 架构师:
Prompt: "你是架构设计师。请阅读 .claude/roles/architect.md 了解职责和模板。
阅读 PRD docs/prd/feature-<FEATURE>.md，编写技术设计文档。
输出到 docs/architecture/feature-<FEATURE>.md。"
Agent 2b - UI 设计师:
Prompt: "你是 UI 设计师。请阅读 .claude/roles/ui-designer.md 了解职责和模板。
阅读 PRD docs/prd/feature-<FEATURE>.md，编写 UI 设计文档。
输出到 docs/ui-design/feature-<FEATURE>.md。"
Agent 2c - 测试工程师（仅计划）:
Prompt: "你是测试工程师。请阅读 .claude/roles/tester.md 了解职责和模板。
阅读 PRD docs/prd/feature-<FEATURE>.md，仅编写测试计划和测试用例文档，不写代码。
输出到 docs/test-plans/feature-<FEATURE>.md。"
As each agent completes, use pipeline_update_phase with phaseId=2 and subtaskRole to update its status.
When all 3 done: use pipeline_update_phase phaseId=2, status="done"
Phase 3: Fullstack
Prompt: "你是全栈工程师。请阅读 .claude/roles/fullstack.md。
阅读上游文档（PRD + 架构 + UI + 测试计划），实现功能「<FEATURE>」代码到 src/。"
Phase 4: Code Review
Prompt: "你是代码审查员。请阅读 .claude/roles/reviewer.md。
审查功能「<FEATURE>」代码，输出到 docs/reviews/feature-<FEATURE>.md。
必须标注严重程度：🔴 Blocker / 🟡 Warning / 🟢 Info。
末尾添加「Blocker 汇总」。无 Blocker 写「无 Blocker 问题」。"
Phase 5: Fix Review
Prompt: "你是全栈工程师。阅读审查报告 docs/reviews/feature-<FEATURE>.md，
修复所有 🔴 Blocker 和 🟡 Warning。输出修复日志到 docs/reviews/feature-<FEATURE>-fix-log.md。"
Skip if review says "无 Blocker 问题".
Phase 6: Test Execution
Prompt: "你是测试工程师。根据测试计划编写测试代码并执行，
输出结果到 docs/test-plans/feature-<FEATURE>-results-round-1.md。
全部通过则在总结中写「全部通过」。"
Phase 7: Fix-Test Loop (max 5 rounds)
for round = 1 to 5:
1. Read latest test results, check if "全部通过" → break
2. Launch Fullstack Agent → fix bugs
3. Launch Tester Agent → retest → results-round-<N+1>.md
4. Use pipeline_update_fix_round with `root` = current working directory to record round result
Step 4: Finalize
Use MCP tool pipeline_finalize with root = current working directory and status "done".
Display summary with all output files.
Subcommand: status
Step 1: Use MCP tool
Call pipeline_status with root = current working directory to get the current pipeline state.
Step 2: Display
Format the JSON response as a visual progress table:
Feature: <name> | Status: <running/done> | Started: <time>
─────────────────────────────────────────────────────
Phase 1 产品经理 ✅ done
Phase 2 并行设计 ✅ done
├─ 架构师 ✅ done (29.9 KB)
├─ UI 设计师 ✅ done (31.0 KB)
└─ 测试工程师 ✅ done (15.2 KB)
Phase 3 全栈开发 🔄 running (12 files)
Phase 4 代码审查 ⏳ pending
Phase 5 审查修复 ⏳ pending
Phase 6 测试执行 ⏳ pending
Phase 7 修复循环 ⏳ pending [_ _ _ _ _]
─────────────────────────────────────────────────────
Step 3: Show next steps
Suggest /agent run <feature> <phase> to resume, or /agent dashboard to monitor.
Subcommand: dashboard
Use MCP tool pipeline_dashboard with action "start", root = current working directory, and optional port (default 3210).
Report the returned URL to the user.
Subcommand: init
Step 1: Ask the user
- Project description — What is this project?
- Tech stack — e.g. "Vue 3 + TypeScript + Hono"
- Roles — Which to include? Default all 6: PM, Architect, UI Designer, Fullstack, Tester, Reviewer
- Language — Documentation language? Default: 中文
Step 2: Initialize
Use MCP tool pipeline_init_project with:
root: current working directory (MUST pass explicitly)techStack: user's answerlanguage: user's answer
Step 3: Summary
Multi-Agent Workflow initialized!
Plugin: @aspect-mark/agent-pipeline (MCP Server)
Project: .claude/roles/{pm,architect,ui-designer,fullstack,tester,reviewer}.md
scripts/pipeline.js (CLI shim)
Quick start:
/agent run <feature> # Full pipeline
/agent run <feature> 3 # From Phase 3
/agent status # Check progress
/agent dashboard # Visual monitoring
