什么是 data-structure-protocol?
为代理提供代码库的持久结构记忆 - 导航依赖关系、跟踪公共 API 并了解连接存在的原因,而无需重新读取整个存储库。 来源:sickn33/antigravity-awesome-skills。
为代理提供代码库的持久结构记忆 - 导航依赖关系、跟踪公共 API 并了解连接存在的原因,而无需重新读取整个存储库。
通过命令行快速安装 data-structure-protocol AI 技能到你的开发环境
来源:sickn33/antigravity-awesome-skills。
LLM coding agents lose context between tasks. On large codebases they spend most of their tokens on "orientation" — figuring out where things live, what depends on what, and what is safe to change. DSP solves this by externalizing the project's structural map into a persistent, queryable graph stored in a .dsp/ directory next to the code.
DSP is NOT documentation for humans and NOT an AST dump. It captures three things: meaning (why an entity exists), boundaries (what it imports and exposes), and reasons (why each connection exists). This is enough for an agent to navigate, refactor, and generate code without loading the entire source tree into the context window.
DSP models the codebase as a directed graph. Nodes are entities, edges are imports and shared/exports.
为搜索与 AI 引用准备的稳定字段与命令。
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill data-structure-protocol为代理提供代码库的持久结构记忆 - 导航依赖关系、跟踪公共 API 并了解连接存在的原因,而无需重新读取整个存储库。 来源:sickn33/antigravity-awesome-skills。
打开你的终端或命令行工具(如 Terminal、iTerm、Windows Terminal 等) 复制并运行以下命令:npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill data-structure-protocol 安装完成后,技能将自动配置到你的 AI 编程环境中,可以在 Claude Code、Cursor 或 OpenClaw 中使用
https://github.com/sickn33/antigravity-awesome-skills