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155 lines
5.8 KiB
155 lines
5.8 KiB
# s05: Skills (技能加载)
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`s01 > s02 > s03 > s04 > [ s05 ] s06 | s07 > s08 > s09 > s10 > s11 > s12`
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> *"用到什么知识, 临时加载什么知识"* -- 通过 tool_result 注入, 不塞 system prompt。
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>
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> **Harness 层**: 按需知识 -- 模型开口要时才给的领域专长。
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## 问题
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你希望智能体遵循特定领域的工作流: git 约定、测试模式、代码审查清单。全塞进系统提示太浪费 -- 10 个技能, 每个 2000 token, 就是 20,000 token, 大部分跟当前任务毫无关系。
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## 解决方案
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```
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System prompt (Layer 1 -- always present):
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+--------------------------------------+
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| You are a coding agent. |
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| Skills available: |
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| - git: Git workflow helpers | ~100 tokens/skill
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| - test: Testing best practices |
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+--------------------------------------+
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When model calls load_skill("git"):
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+--------------------------------------+
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| tool_result (Layer 2 -- on demand): |
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| <skill name="git"> |
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| Full git workflow instructions... | ~2000 tokens
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| Step 1: ... |
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| </skill> |
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+--------------------------------------+
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```
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第一层: 系统提示中放技能名称 (低成本)。第二层: tool_result 中按需放完整内容。
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## 工作原理
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1. 每个技能是一个目录, 包含 `SKILL.md` 文件和 YAML frontmatter。
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```
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skills/
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pdf/
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SKILL.md # ---\n name: pdf\n description: Process PDF files\n ---\n ...
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code-review/
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SKILL.md # ---\n name: code-review\n description: Review code\n ---\n ...
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```
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2. SkillLoader 递归扫描 `SKILL.md` 文件, 用目录名作为技能标识。
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```java
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public class SkillLoader {
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private static final Pattern FRONTMATTER_PATTERN =
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Pattern.compile("^---\\n(.*?)\\n---\\n(.*)", Pattern.DOTALL);
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private final Map<String, SkillInfo> skills = new LinkedHashMap<>();
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record SkillInfo(Map<String, String> meta, String body, String path) {}
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public SkillLoader(Path skillsDir) {
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loadAll(skillsDir);
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}
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/** 递归扫描 skills 目录下所有 SKILL.md 文件 */
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private void loadAll(Path skillsDir) {
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if (!Files.exists(skillsDir)) return;
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try (Stream<Path> paths = Files.walk(skillsDir)) {
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paths.filter(p -> p.getFileName().toString().equals("SKILL.md"))
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.sorted()
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.forEach(p -> {
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String text = Files.readString(p);
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var parsed = parseFrontmatter(text);
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String name = parsed.meta().getOrDefault("name",
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p.getParent().getFileName().toString());
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skills.put(name, new SkillInfo(
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parsed.meta(), parsed.body(), p.toString()));
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});
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}
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}
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/** Layer 1: 获取所有技能的简短描述（用于系统提示注入） */
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public String getDescriptions() {
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if (skills.isEmpty()) return "(no skills available)";
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StringBuilder sb = new StringBuilder();
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for (var entry : skills.entrySet()) {
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String desc = entry.getValue().meta()
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.getOrDefault("description", "No description");
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sb.append(" - ").append(entry.getKey())
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.append(": ").append(desc).append("\n");
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}
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return sb.toString().stripTrailing();
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}
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/** Layer 2: 加载指定技能的完整内容（作为 @Tool 方法） */
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@Tool(description = "Load specialized knowledge by name.")
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public String loadSkill(
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@ToolParam(description = "Skill name to load") String name) {
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SkillInfo skill = skills.get(name);
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if (skill == null)
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return "Error: Unknown skill '" + name + "'. Available: "
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+ String.join(", ", skills.keySet());
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return "<skill name=\"" + name + "\">\n"
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+ skill.body() + "\n</skill>";
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}
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}
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```
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3. 第一层写入系统提示。第二层通过 SkillLoader 上的 `@Tool` 注解方法按需加载。
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```java
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public S05SkillLoading(ChatModel chatModel) {
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Path skillsDir = Path.of(System.getProperty("user.dir"), "skills");
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SkillLoader skillLoader = new SkillLoader(skillsDir);
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// Layer 1: 技能元数据注入系统提示
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String system = "You are a coding agent at " + System.getProperty("user.dir") + ".\n"
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+ "Use loadSkill to access specialized knowledge.\n\n"
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+ "Skills available:\n"
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+ skillLoader.getDescriptions();
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this.chatClient = ChatClient.builder(chatModel)
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.defaultSystem(system)
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.defaultTools(
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new BashTool(), new ReadFileTool(),
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new WriteFileTool(), new EditFileTool(),
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skillLoader // Layer 2: loadSkill @Tool 方法
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)
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.build();
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}
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```
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模型知道有哪些技能 (便宜), 需要时再加载完整内容 (贵)。
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## 相对 s04 的变更
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| 组件 | 之前 (s04) | 之后 (s05) |
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|----------------|------------------|--------------------------------|
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| Tools | 5 (基础 + task) | 5 (基础 + load_skill) |
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| 系统提示 | 静态字符串 | + 技能描述列表 |
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| 知识库 | 无 | skills/\*/SKILL.md 文件 |
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| 注入方式 | 无 | 两层 (系统提示 + result) |
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## 试一试
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```sh
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cd learn-claude-code
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mvn exec:java -Dexec.mainClass=io.mybatis.learn.s05.S05SkillLoading
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```
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试试这些 prompt (英文 prompt 对 LLM 效果更好, 也可以用中文):
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1. `What skills are available?`
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2. `Load the agent-builder skill and follow its instructions`
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3. `I need to do a code review -- load the relevant skill first`
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4. `Build an MCP server using the mcp-builder skill`
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