asgeirtj/system_prompts_leaks
A maintained archive of 100+ products’ system prompts exposes how coding-agent vendors structure tools, skills, memory, safety, and behavior—useful reference material for harness design.
The repository maintains extracted system prompts from **100+ AI products**, including Claude Code, Codex, Cursor, Gemini, Copilot, and several research agents. It also archives subagent prompts, skills, tool instructions, memory rules, and reasoning variants.
Use the captures as implementation references when designing agent harnesses or debugging behavior your own prompt does not explain. Claude Design’s bundle of **53 tools**, **22 skills**, and **10 starter components** is a particularly concrete example of how a product divides instructions from capabilities.
The repository maintains extracted system prompts from **100+ AI products**, including Claude Code, Codex, Cursor, Gemini, Copilot, and several research agents. It also archives subagent prompts, skills, tool instructions, memory rules, and reasoning variants. Use the captures as implementation references when designing agent harnesses or debugging behavior your own prompt does not explain. Claude Design’s bundle of **53 tools**, **22 skills**, and **10 starter components** is a particularly concrete example of how a product divides instructions from capabilities. The archive mixes recent captures with old models and deprecated features, so version and product context matter. Extracted prompts reveal vendor instruction patterns, but the material alone does not establish which patterns improve agent outcomes.
This supplies a comparative evidence base for how real products partition prompts, tools, skills, memory, and subagents, making unexplained harness behavior easier to investigate. It does not show that copied patterns work: captures must be tied to their product and model version, then tested against an explicit behavioral contract rather than treated as current best practice.