context-management-context-restore
使用语义记忆恢复AI上下文
此技能帮助AI助手在复杂工作流中恢复和重建项目上下文，使长期运行的任务能够无缝继续，而不会丢失关键信息。
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正在使用“context-management-context-restore”。 How do I implement context restoration for my AI project?
预期结果:
To implement context restoration, follow these core steps: 1) Identify your context storage location (vector DB or file system), 2) Choose restoration mode (full/incremental/diff), 3) Set token budget and relevance threshold, 4) Apply semantic retrieval strategies, 5) Validate restored context against codebase. Would you like me to elaborate on any specific step?
正在使用“context-management-context-restore”。 What strategies help maintain context quality?
预期结果:
Key strategies include: semantic vector search with cosine similarity, multi-stage relevance scoring with temporal decay, incremental context loading to manage token budgets, and cryptographic context signatures for integrity verification. Would you like detailed implementation guidance for any of these?
安全审计
安全This skill is a documentation/guide file containing no executable code. Static findings for 'external_commands' and 'weak cryptographic algorithm' are false positives - the flagged lines contain markdown documentation, code examples in fenced blocks, and YAML frontmatter, not actual shell execution or cryptographic implementations.
高风险问题 (2)
质量评分
你能构建什么
恢复复杂的AI项目
当在中断后返回到长期运行的AI项目时，使用此技能重建完整上下文，包括决策、架构和当前状态。
跨项目知识转移
在相关项目之间转移语义知识和上下文，保持一致性并保留架构决策。
多代理工作流协调
使多个AI代理能够共享和恢复上下文，在复杂的协作工作流中保持一致的决策轨迹。
试试这些提示
I need to restore context for project [project-name]. The context is stored at [storage-location]. Please guide me through the restoration process using full restoration mode.
Help me implement incremental context restoration for my project. I want to update only the changed components since my last session.
I need to retrieve specific context about [topic] from my project. Show me how to use semantic vector search to find the most relevant information.
Guide me through validating restored context against the current codebase. I want to ensure consistency and integrity before continuing work.
最佳实践
- 在继续工作之前，始终根据当前代码库验证恢复的上下文
- 使用语义相似度阈值（0.75+）来过滤不相关的上下文组件
- 尽可能使用增量更新而非完全恢复以节省代币
避免
- 不经过相关性过滤恢复完整上下文 - 导致代币溢出
- 跳过上下文验证 - 可能重新引入过时或不一致的信息
- 忽视代币预算限制 - 导致上下文截断和信息丢失