This prompt requires a structured design for a multi-agent system. The expected output is a JSON object or clearly delineated sections containing:
1. A specific 'System Prompt' for each of the four agents (Planner, Coding, Reviewer, QA).
2. A 'MCP Server Configuration' section detailing the exact setup needed for agents to access the file system, terminal, and PostgreSQL database. Ensure all details are precise and complete.
Dev prompt for Multi-Agent System Design for Admin Dashboard
AI prompt created by PromptsRadar
Instructions
PromptsRadar
2026-05-12
Claude
As a Principal Architect, design a multi-agent system, leveraging the Model Context Protocol (MCP), to fully automate the implementation of a new feature within a full-stack TypeScript monorepo.
Project Context:
- Monorepo Stack: Next.js 15 (frontend), NestJS (backend).
- Database: PostgreSQL, using Drizzle ORM for schema definitions and migrations.
- UI Framework: Tailwind CSS v4.
- Access Control: Role-Based Access Control (RBAC) implemented with CASL.
- Development Standards: Agents must strictly adhere to project-specific STYLE_GUIDE.md and AGENTS.md for all coding and interaction guidelines.
Feature Request:
Automate the complete development of an administrative dashboard for managing user roles and permissions.
Agent Architecture & Responsibilities:
1. Planner Agent:
- Input: The user story (feature request).
- Task: Deconstruct the user story into granular, actionable sub-tasks.
- Output: A tasks.json file detailing all required routes, database schema changes, UI components, and associated tests.
2. Coding Agent:
- Input: The tasks.json plan from the Planner Agent, and error logs from the Reviewer Agent.
- Task: Generate all necessary code for the specified feature, strictly following STYLE_GUIDE.md and AGENTS.md. console.log is permitted for debugging purposes only; no production logging.
- Constraint: If the agent enters a development loop, failing to progress after 5 attempts, it must generate a DEBUG_LOG.md explaining the failure mode and cease operations.
3. Reviewer Agent:
- Input: Code artifacts produced by the Coding Agent.
- Task: Execute npm run lint and npm run test on the generated codebase.
- Output: If tests or linting fail, forward the error log back to the Coding Agent for remediation. If successful, pass the validated code to the QA Agent.
4. QA Agent:
- Input: Verified code from the Reviewer Agent.
- Task: Develop comprehensive Playwright E2E tests for the new UI components and ensure their successful execution in headless mode.
- Output: A final pass/fail status for the E2E tests.
Overall Constraint:
- The entire development process must require zero manual coding intervention from the user.
Deliverables:
Provide the following:
1. System Prompt for Each Agent: A distinct, detailed system prompt for each of the four agent types (Planner, Coding, Reviewer, QA).
2. MCP Server Configuration: The necessary Model Context Protocol (MCP) server configuration to grant agents secure access to the file system, terminal, and PostgreSQL database.
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