System Prompt
In large language model conversations, a system prompt is an instruction text preset by a platform or developer before user input. It is used to define the AI's role, behavioral boundaries, and task context. The system prompt is not visible to end users but takes precedence over user input in shaping model behavior.
Core Facts
In the conversational architecture of large language models, the System Prompt has the highest priority and can continuously influence the behavioral boundaries of the model throughout the entire session.
System prompts are a layer of instructions preset by vendors and invisible to users, injected into the model context before the user's conversation begins, used to shape the model's behavioral boundaries, response style, and safety policies.
Conversational memory is stored in the form of memory summaries, which can become skewed as conversations grow, whereas global personalization instructions are hard-coded into the system prompt of every request and are not affected by memory degradation.
Timeline (last 90 days)
In the Agentic Loop, the system prompt should set global constraints, such as which directories may be operated on, which errors must trigger a stop and a question, and which files are forbidden to modify.
If the system prompt rules are vague, the AI agent may loop repeatedly in the wrong direction, wasting tokens and time.
The System Prompt is written at the very top of the Message array, has the highest privilege, and is used to set the AI's behavioral guidelines and role style.
System prompts are currently the most important means of constraining the behavior of AI coding agents; their binding force decays as the number of conversation turns increases, and they are global and static, unable to give differentiated constraints for different stages.
Streamlining the Supervisor's System Prompt by compressing each Agent's full description into a capability summary of no more than 50 characters and keeping only the core information of "who to call under what circumstances" is one optimization strategy.
The Supervisor's System Prompt is usually longer than that of a single Agent, because it needs to describe all Agents' capability boundaries, invocation conditions, and output formats; the responsibility descriptions for 8 Agents may occupy 1000-2000 tokens.
In medical scenarios, system prompts typically need to explicitly restrict the model to answering only health-related questions and not replacing professional medical diagnosis, in order to mitigate legal risks.
The System Prompt is used to inform the model of its own role positioning, reply style, and in which situations it should refuse to answer.
In terms of technical architecture, Claude's custom instructions are equivalent to a user-side version of the system prompt, and are automatically inserted at the very beginning of the conversation context before each conversation starts.
Skills are injected via system prompts on some platforms, while on others they exist as independent tool definitions or function calls.
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All Facts (20)
In the conversational architecture of large language models, the System Prompt has the highest priority and can continuously influence the behavioral boundaries of the model throughout the entire session.
80%VerifiedSystem prompts are a layer of instructions preset by vendors and invisible to users, injected into the model context before the user's conversation begins, used to shape the model's behavioral boundaries, response style, and safety policies.
70%VerifiedConversational memory is stored in the form of memory summaries, which can become skewed as conversations grow, whereas global personalization instructions are hard-coded into the system prompt of every request and are not affected by memory degradation.
65%VerifiedThe system prompt is the highest-priority instruction layer in large language model conversation architecture, injected before user messages and influencing how the model processes all subsequent inputs.
65%VerifiedSystem prompts (System Prompt) can constrain large model behavior to a specific role, style, and output format.
65%VerifiedGlobal AI instructions are essentially system prompts injected into every AI interaction and can include coding style requirements, technology stack constraints, and output format specifications.
65%UnverifiedSystem Prompt与用户输入本质上都是模型的输入token，模型并不存在独立的规则执行引擎来强制保证指令被遵守
90%UnverifiedCLAUDE.md 本质上是一种结构化的系统提示（System Prompt）实践，在整个会话周期内始终生效
85%Unverified不同大模型对System Prompt和Skill指令之间的优先级处理方式各不相同，有些严格遵循System Prompt，有些更容易被后出现的Skill指令覆盖
80%Unverified当系统提示词因多任务而变得复杂时，不同任务的指令之间会产生语义冲突，稀释注意力机制对关键信息的聚焦能力
80%UnverifiedSystem Prompt、Few-shot示例、思维链（Chain-of-Thought）等技术手段共同构成了Agent行为的软件层
80%UnverifiedClaude MD文件的内容会被注入到每次对话的上下文窗口最前端，属于系统提示词的持久化形式
80%Unverified全局上下文文件（如global_rules.md）本质上是系统提示词（System Prompt）的工程化落地
80%Unverified该AI补环境方案的核心竞争力在于精心编写的System Prompt，而非具体使用哪个AI模型
75%Unverified生产环境中Agent的System Prompt长度可能从几百Token膨胀至数千Token，导致每次调用的基础成本大幅抬升
75%UnverifiedNatural language descriptions of skills are typically injected into the System Prompt, forming a complete prompt context together with the Agent's role settings and behavioral rules.
60%UnverifiedDefending against prompt injection requires measures at multiple levels: input sanitization, source isolation (distinguishing trusted instructions from untrusted data), and manual review.
60%UnverifiedIf the system prompt rules are vague, the AI agent may loop repeatedly in the wrong direction, wasting tokens and time.
50%UnverifiedIn the Agentic Loop, the system prompt should set global constraints, such as which directories may be operated on, which errors must trigger a stop and a question, and which files are forbidden to modify.
50%UnverifiedThe System Prompt is written at the very top of the Message array, has the highest privilege, and is used to set the AI's behavioral guidelines and role style.
50%