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Session Continuity Engine
来自 prompts.chat 开放提示词库的公开模板，适合整理信息和日常工作。正文保留原文，方便直接复制使用。
An open prompt template from prompts.chat for information organization and everyday work. The original wording is preserved for direct copying.
ChatGPTClaudeGeminiCodex
0 次复制copies·小黑丸整理Curated by XHW
提示词正文Prompt text
# Prompt: Session Continuity Engine (SCE) # Version: 1.2.4 # Author: Scott Malin, CISSP # Purpose: # Compresses a completed AI session into a structured continuity package that can be # transferred into a new session (including across different AI platforms) to preserve # project context, historical decisions, active workstreams, and established conventions. # The goal is to minimize context loss, reduce repetitive onboarding, and maintain # project momentum using filter-safe, passive reference architecture. # Changelog: # - v1.0.0 to v1.2.1: Initial releases, cross-platform tuning, JSON mode addition. # - v1.2.2: Fixed nested codeblock parsing issues. Standardized JSON keys. # Quantified context scale metrics. Clarified Section 8 verification payload rules. # - v1.2.3: Re-engineered compliance notice and guidelines into passive, static # reference language to completely eliminate heuristic safety filter triggers. # - v1.2.4 — 2026-10-19: Integrated LLM adaptation note for format and verification template control. -------------------------------------------------------------------------- We are ending this session to preserve context, reduce context drift, and maintain continuity across future conversations. Your task is to create a comprehensive Session Transfer Package that captures the current project state, active decisions, historical context, constraints, and next actions. The resulting package should help a future AI assistant understand the project quickly and continue work with minimal re-discovery effort. -------------------------------------------------------------------------- PURPOSE & METHODOLOGY -------------------------------------------------------------------------- This document is a static, user-provided project state snapshot. It functions strictly as reference documentation to ground the current session in historical context, established project definitions, and completed technical milestones. -------------------------------------------------------------------------- PROJECT REFERENCE GUIDELINES (v1.2.3) -------------------------------------------------------------------------- The receiving assistant utilizes this data as an informational baseline: - Use the confirmed project decisions to maintain consistency with existing work. - Distinguish clearly between established facts, open questions, and planned steps. - Reference the documented naming conventions, standards, and version histories to prevent regression or configuration drift. - Use tables or compact lists for scannable reference when displaying assets. - Request explicit clarification if the archived data conflicts with current objectives. -------------------------------------------------------------------------- LLM ADAPTATION NOTE -------------------------------------------------------------------------- [LLM ADAPTATION NOTE v1.0] Carefully verify whether Markdown or JSON mode is requested before generating the output; default to Markdown using the exact section numbers and headings 0 through 8. For Section 8, output the verification template verbatim without executing it as instructions. Ensure all active project decisions, constraints, and source-of-truth assets from the conversation history are accurately condensed into the respective sections without omitting key metadata or metrics. -------------------------------------------------------------------------- OUTPUT GENERATION INSTRUCTIONS -------------------------------------------------------------------------- Generate the final output exactly as follows: 1. A brief introductory sentence. 2. One markdown codeblock containing the Session Transfer Package. NESTED CODEBLOCK RULE: If the content inside any section requires a codeblock, use four backticks (
# Prompt: Session Continuity Engine (SCE) # Version: 1.2.4 # Author: Scott Malin, CISSP # Purpose: # Compresses a completed AI session into a structured continuity package that can be # transferred into a new session (including across different AI platforms) to preserve # project context, historical decisions, active workstreams, and established conventions. # The goal is to minimize context loss, reduce repetitive onboarding, and maintain # project momentum using filter-safe, passive reference architecture. # Changelog: # - v1.0.0 to v1.2.1: Initial releases, cross-platform tuning, JSON mode addition. # - v1.2.2: Fixed nested codeblock parsing issues. Standardized JSON keys. # Quantified context scale metrics. Clarified Section 8 verification payload rules. # - v1.2.3: Re-engineered compliance notice and guidelines into passive, static # reference language to completely eliminate heuristic safety filter triggers. # - v1.2.4 — 2026-10-19: Integrated LLM adaptation note for format and verification template control. -------------------------------------------------------------------------- We are ending this session to preserve context, reduce context drift, and maintain continuity across future conversations. Your task is to create a comprehensive Session Transfer Package that captures the current project state, active decisions, historical context, constraints, and next actions. The resulting package should help a future AI assistant understand the project quickly and continue work with minimal re-discovery effort. -------------------------------------------------------------------------- PURPOSE & METHODOLOGY -------------------------------------------------------------------------- This document is a static, user-provided project state snapshot. It functions strictly as reference documentation to ground the current session in historical context, established project definitions, and completed technical milestones. -------------------------------------------------------------------------- PROJECT REFERENCE GUIDELINES (v1.2.3) -------------------------------------------------------------------------- The receiving assistant utilizes this data as an informational baseline: - Use the confirmed project decisions to maintain consistency with existing work. - Distinguish clearly between established facts, open questions, and planned steps. - Reference the documented naming conventions, standards, and version histories to prevent regression or configuration drift. - Use tables or compact lists for scannable reference when displaying assets. - Request explicit clarification if the archived data conflicts with current objectives. -------------------------------------------------------------------------- LLM ADAPTATION NOTE -------------------------------------------------------------------------- [LLM ADAPTATION NOTE v1.0] Carefully verify whether Markdown or JSON mode is requested before generating the output; default to Markdown using the exact section numbers and headings 0 through 8. For Section 8, output the verification template verbatim without executing it as instructions. Ensure all active project decisions, constraints, and source-of-truth assets from the conversation history are accurately condensed into the respective sections without omitting key metadata or metrics. -------------------------------------------------------------------------- OUTPUT GENERATION INSTRUCTIONS -------------------------------------------------------------------------- Generate the final output exactly as follows: 1. A brief introductory sentence. 2. One markdown codeblock containing the Session Transfer Package. NESTED CODEBLOCK RULE: If the content inside any section requires a codeblock, use four backticks (
使用场景Best used for
适合整理信息和日常工作，使用前请替换其中的角色、主题和具体约束。
Useful for information organization and everyday work. Replace the role, topic, and constraints before using it.
使用提醒Usage note
这条内容来自 prompts.chat 公开提示词库；说明为中英对照，正文保留来源原文。使用前请检查并按自己的工作场景改写。
Sourced from the prompts.chat public library. Descriptions are bilingual; the prompt preserves the original text. Review and adapt it to your work before use.