Anthropic's System Prompt for Claude Leaked on GitHub
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Anthropic's System Prompt for Claude Leaked on GitHub

Woo Hyung Choi
2026.01.14
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#LLM#System Prompt#AI Behavior#Anthropic#Claude

Key Points

  • 1A recent leak on GitHub exposed Anthropic's extensive 24,000-token system prompt for Claude, detailing the AI's internal instructions for thought processes and response generation.
  • 2The leaked document specifically reveals three key functional areas: model behavior guidelines, tool usage protocols, and citation formatting rules.
  • 3This incident provides valuable insight into how sophisticated AI systems are governed by detailed internal frameworks and policies, highlighting that their output is a product of deliberate design, not just inherent intelligence.

The document reports on the recent unauthorized disclosure, via GitHub, of Anthropic's comprehensive system prompt for its AI model, Claude. This extensive internal instruction set, approximately 24,000 tokens in length, is deemed highly significant as it unveils the core architectural framework that governs Claude's operational paradigm, encompassing its cognitive processes, external tool interaction, and response generation methodologies.

The leaked documentation explicitly details three critical functional components that regulate Claude's behavior and output:

  1. Model Behavior Guidelines: These constitute a set of prescriptive and proscriptive directives that define the permissible scope and ethical boundaries of the AI's responses. They specify preferred conversational styles, information handling protocols, safety constraints, and adherence to specific personas or principles, thereby shaping the model's fundamental interaction paradigm.
  2. Tool Usage Protocols: This section outlines the precise procedural specifications and conditions under which Claude is authorized to invoke and integrate external utilities or Application Programming Interfaces (APIs). It details the decision-making logic for tool selection, the format for data exchange between the model and the tool (inputs and outputs), error handling mechanisms, and the subsequent incorporation of tool-derived information into the model's final response generation.
  3. Citation Formatting Rules: These are explicit formatting specifications for how Claude is to attribute sources or integrate external information, ensuring consistency, accuracy, and adherence to predefined citation standards in its generated outputs.

This incident offers an exceptional insight into Anthropic's sophisticated control framework for its AI systems. It underscores that the observed intelligence and consistency in AI responses are not merely emergent properties of a large language model but are meticulously engineered through detailed internal rules, policy directives, and systematic design principles, shifting the perception of AI from an opaque "black box" to a highly regulated and deliberately constructed artifact.