design_system_architecture
Design a complete system architecture based on requirements: includes component breakdown, data flow patterns, technology recommendations, and deployment strategies.
Instructions
Design a complete system architecture based on requirements using GLM-4.6. Provides component breakdown, data flow patterns, technology recommendations, and deployment strategies.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| requirements | Yes | Detailed system requirements, constraints, and objectives |
Implementation Reference
- src/index.ts:65-78 (schema)Tool schema definition for 'design_system_architecture' including name, description, and inputSchema (requires 'requirements' string).
{ name: 'design_system_architecture', description: 'Design a complete system architecture based on requirements using GLM-4.6. Provides component breakdown, data flow patterns, technology recommendations, and deployment strategies.', inputSchema: { type: 'object', properties: { requirements: { type: 'string', description: 'Detailed system requirements, constraints, and objectives', }, }, required: ['requirements'], }, }, - src/index.ts:172-183 (handler)Tool call handler for 'design_system_architecture' - extracts 'requirements' from args and delegates to glmClient.designSystemArchitecture().
case 'design_system_architecture': { const { requirements } = args as { requirements: string }; const response = await glmClient.designSystemArchitecture(requirements); return { content: [ { type: 'text', text: response, }, ], }; } - src/index.ts:24-119 (registration)All tools are registered via the 'tools' array (line 24) passed to ListToolsRequestSchema handler (line 134). The 'design_system_architecture' tool is entry at index 2 in this array.
const tools: Tool[] = [ { name: 'consult_architecture', description: 'Consult GLM-4.6 for expert software architecture guidance, system design patterns, scalability strategies, and technical decision-making. Use this for high-level architectural questions requiring deep technical expertise.', inputSchema: { type: 'object', properties: { query: { type: 'string', description: 'The architectural question or problem requiring expert consultation', }, context: { type: 'string', description: 'Optional additional context about the system, requirements, or constraints', }, }, required: ['query'], }, }, { name: 'analyze_code_architecture', description: 'Analyze code from an architectural perspective using GLM-4.6. Evaluates design patterns, SOLID principles, scalability, security implications, and provides improvement recommendations.', inputSchema: { type: 'object', properties: { code: { type: 'string', description: 'The source code to analyze', }, language: { type: 'string', description: 'Programming language of the code (e.g., typescript, python, go, java)', }, question: { type: 'string', description: 'Specific architectural question about the code', }, }, required: ['code', 'language', 'question'], }, }, { name: 'design_system_architecture', description: 'Design a complete system architecture based on requirements using GLM-4.6. Provides component breakdown, data flow patterns, technology recommendations, and deployment strategies.', inputSchema: { type: 'object', properties: { requirements: { type: 'string', description: 'Detailed system requirements, constraints, and objectives', }, }, required: ['requirements'], }, }, { name: 'review_technical_decision', description: 'Review and evaluate a technical decision using GLM-4.6 architectural expertise. Assesses impact, trade-offs, alternatives, risks, and provides recommendations.', inputSchema: { type: 'object', properties: { decision: { type: 'string', description: 'The technical decision to review', }, context: { type: 'string', description: 'Context including current architecture, constraints, and objectives', }, }, required: ['decision', 'context'], }, }, { name: 'advanced_reasoning', description: 'Consult GLM-4.6 for advanced mathematical, algorithmic, and scientific reasoning tasks. Delivers world-class innovative solutions with rigorous methodology, optimal algorithms, and enterprise-grade quality. Use for: complex algorithms, mathematical proofs, performance optimization, advanced data structures, computational problems, scientific analysis. Response optimized for Claude 4.5 Sonnet with XML structure.', inputSchema: { type: 'object', properties: { task: { type: 'string', description: 'The specific mathematical, algorithmic, or scientific task requiring advanced reasoning', }, context: { type: 'string', description: 'Comprehensive context including: problem domain, constraints, requirements, current approach (if any), performance requirements, business logic', }, expected_outcome: { type: 'string', description: 'Detailed description of expected outcome: solution characteristics, performance targets, quality metrics, innovation requirements', }, }, required: ['task', 'context', 'expected_outcome'], }, }, ]; - src/glm-client.ts:143-157 (helper)The designSystemArchitecture method in GLMClient which constructs a structured query prompt from the requirements and delegates to consultArchitecture() for the actual LLM call.
async designSystemArchitecture(requirements: string): Promise<string> { const query = `Design a system architecture based on the following requirements: ${requirements} Provide: 1. High-level architecture diagram description 2. Component breakdown and responsibilities 3. Data flow and communication patterns 4. Technology stack recommendations 5. Scalability and deployment strategy 6. Security architecture considerations`; return this.consultArchitecture(query); }