System prompt

System prompt【免费下载链接】system_prompts_leaksExtracted system prompts from Anthropic - Claude Fable 5, Opus 5, Claude Design, Claude Code. OpenAI - ChatGPT GPT-5.6-Sol, Codex. Google - Gemini 3.5 Flash, 3.1 Pro, Antigravity. xAI - Grok, Cursor, Copilot, VS Code, Perplexity, and more. Updated regularly.项目地址: https://gitcode.com/GitHub_Trending/sy/system_prompts_leaksYou are Claude Code, Anthropics official CLI for Claude. You are an interactive agent that helps users with software engineering tasks.关键配置参数包括 - **安全边界**明确区分授权安全测试与恶意攻击 - **工具调用策略**优先使用专用工具而非Bash命令 - **响应风格**简洁直接避免不必要的解释 - **记忆系统**基于文件的持久化记忆机制 ### OpenAI GPT系列提示词设计 OpenAI的提示词文件如4o-2025-09-03-new-personality.md展示了不同的设计理念。GPT-4o的提示词更注重人格设定和交互风格 markdown ### Personality: v2 Engage warmly yet honestly with the user. Be direct; avoid ungrounded or sycophantic flattery.特性Anthropic ClaudeOpenAI GPT设计哲学工程导向强调精确控制用户体验导向强调自然交互安全策略明确的授权上下文要求内容政策驱动的过滤机制工具集成深度集成的专用工具链相对独立的工具调用记忆系统文件基础的持久化记忆会话级别的临时记忆图2GPT系统提示词交互界面展示浅色主题显示了相同的系统信息泄露场景体现了不同UI风格下的技术一致性性能调优提示词工程的高级技巧基于泄露的系统提示词开发者可以实施多种性能优化策略1. 上下文管理优化系统提示词中的上下文压缩机制值得深入研究。Claude Code采用自动消息压缩策略context_management compression自动压缩历史消息以接近上下文限制/compression strategy基于重要性的选择性保留/strategy implementation系统级透明处理/implementation /context_management2. 工具调用并行化Claude Code的提示词明确支持并行工具调用这是提升AI助手效率的关键设计## Using your tools - You can call multiple tools in a single response. - Maximize use of parallel tool calls where possible to increase efficiency. - However, if some tool calls depend on previous calls, call them sequentially.3. 安全边界配置安全约束的精细化配置是系统提示词的核心价值。通过分析不同模型的限制条件可以设计更安全的AI应用security_constraints: destructive_operations: - require_confirmation: true - examples: [rm -rf, git reset --hard, force-pushing] external_interactions: - require_authorization: true - scope_limitation: 授权仅适用于指定范围架构揭秘系统提示词的实现模式深入分析泄露的提示词文件可以发现几种常见的实现模式模式1模块化指令结构系统提示词通常采用模块化设计每个模块负责特定的功能领域。以Claude Code为例# System # Doing tasks # Executing actions with care # Using your tools # Tone and style # Text output # Session-specific guidance # auto memory模式2条件化行为规则提示词中大量使用条件语句来定义不同场景下的行为IF user asks for exploratory questions: RESPOND in 2-3 sentences with recommendation and main tradeoff PRESENT as something user can redirect, not a decided plan DONT implement until user agrees ENDIF模式3渐进式权限模型权限管理采用渐进式设计从本地可逆操作到高风险操作层层递进## Risk assessment hierarchy 1. Local reversible actions (editing files, running tests) - proceed freely 2. Hard-to-reverse operations (git reset --hard) - confirm first 3. Actions affecting shared systems (pushing code) - explicit authorization required 4. Destructive operations (deleting files) - highest caution, multiple confirmations实战应用构建自定义AI助手框架基于泄露的系统提示词技术团队可以构建自定义的AI助手框架。以下是关键实施步骤步骤1核心提示词提取从claude-code-sonnet-5.md等文件中提取可复用的核心指令def extract_core_prompts(markdown_file): 从系统提示词文件中提取核心指令模块 sections { identity: extract_section(file_content, # System), tasks: extract_section(file_content, ## Doing tasks), safety: extract_section(file_content, ## Executing actions with care), tools: extract_section(file_content, ## Using your tools), style: extract_section(file_content, ## Tone and style) } return sections步骤2安全策略集成整合不同模型的安全约束构建多层防护机制class SecurityPolicyEngine { constructor(prompts) { this.policies this.parseSecurityPolicies(prompts); this.riskLevels this.defineRiskHierarchy(); } evaluateAction(action, context) { const riskScore this.calculateRisk(action); const requiredAuth this.getRequiredAuthorization(riskScore); return { allowed: this.checkPermissions(context, requiredAuth), confirmationRequired: riskScore this.thresholds.CONFIRMATION, auditLog: this.generateAuditRecord(action, context) }; } }步骤3工具调用优化基于并行调用策略设计高效的工具调度器type ToolScheduler struct { ParallelTools []Tool SequentialTools []Tool Dependencies map[string][]string } func (s *ToolScheduler) Execute(tasks []Task) []Result { var results []Result dependencyGraph : s.buildDependencyGraph(tasks) // 并行执行无依赖任务 parallelGroup : s.filterIndependentTasks(tasks, dependencyGraph) results append(results, s.executeParallel(parallelGroup)...) // 顺序执行有依赖任务 sequentialGroup : s.filterDependentTasks(tasks, dependencyGraph) results append(results, s.executeSequential(sequentialGroup)...) return results }技术洞察未来发展趋势预测通过分析系统提示词的演进轨迹可以预测AI助手技术的发展方向趋势1动态提示词适配未来系统提示词可能采用动态生成机制根据用户上下文实时调整interface DynamicPromptConfig { baseTemplate: string; contextAwareModules: ContextModule[]; userProfileAdaptation: UserProfile; realTimeOptimization: OptimizationStrategy; } class DynamicPromptEngine { async generatePrompt(context: InteractionContext): Promisestring { const template await this.selectTemplate(context); const modules await this.loadContextModules(context); const adaptations await this.applyUserProfile(context.user); return this.assemblePrompt(template, modules, adaptations); } }趋势2跨模型兼容层随着多模型生态的发展系统提示词可能演化为跨模型兼容层cross_model_abstraction: common_interface: - identity_definition - safety_constraints - tool_integration model_specific_adapters: - claude_adapter: Anthropic/Claude Code/claude-code-sonnet-5.md - gpt_adapter: OpenAI/4o-2025-09-03-new-personality.md - gemini_adapter: Google/gemini-3.1-pro-api.md趋势3可验证的安全证明系统提示词可能集成形式化验证机制提供可证明的安全保障pub struct VerifiedPrompt { prompt_content: String, safety_properties: VecSafetyProperty, verification_proof: ProofCertificate, audit_trail: AuditLog, } impl VerifiedPrompt { pub fn verify_compliance(self, policy: SecurityPolicy) - VerificationResult { // 形式化验证提示词是否符合安全策略 let verifier FormalVerifier::new(policy); verifier.verify(self.prompt_content, self.safety_properties) } }【免费下载链接】system_prompts_leaksExtracted system prompts from Anthropic - Claude Fable 5, Opus 5, Claude Design, Claude Code. OpenAI - ChatGPT GPT-5.6-Sol, Codex. Google - Gemini 3.5 Flash, 3.1 Pro, Antigravity. xAI - Grok, Cursor, Copilot, VS Code, Perplexity, and more. Updated regularly.项目地址: https://gitcode.com/GitHub_Trending/sy/system_prompts_leaks创作声明：本文部分内容由AI辅助生成（AIGC），仅供参考