Spring AI 框架下接入 agent skill 手把手教程
参考文档：Spring AI Agentic Patterns (Part 1): Agent Skills - Modular, Reusable Capabilities
引言
点进来的读者应该都了解了 agent skills 是什么，为什么会出现这种工程手段等等，此处不在多说，本篇博客聚焦于在 Spring-AI 下如何快速接入 Skills，并且探究背后实现的原理。
项目示例代码可以在 https://github.com/MimicHunterZ/PocketMind/tree/master/backend/src/main/java/com/doublez/pocketmindserver/demo 下查看，如果觉得项目不错，欢迎给我star~
环境准备
maven依赖
根据官方手册，skill 需要 Spring-AI 2.0.0-M2 版本以上，所以根据这个配置，项目demo的依赖如下：
<parent><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-parent</artifactId><version>4.0.2</version><relativePath/></parent><properties><java.version>21</java.version><spring-ai.version>2.0.0-M2</spring-ai.version></properties><dependencies><dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-web</artifactId></dependency><dependency><groupId>org.springframework.ai</groupId><artifactId>spring-ai-starter-model-openai</artifactId></dependency><!--引入社区实现的 skills 工具--><dependency><groupId>org.springaicommunity</groupId><artifactId>spring-ai-agent-utils</artifactId><version>0.4.2</version></dependency></dependencies><dependencyManagement><dependencyManagement><dependencies><dependency><groupId>org.springframework.ai</groupId><artifactId>spring-ai-bom</artifactId><version>${spring-ai.version}</version><type>pom</type><scope>import</scope></dependency></dependencies></dependencyManagement><repositories><repository><id>spring-milestones</id><name>Spring Milestones</name><url>https://repo.spring.io/milestone</url></repository></repositories>实测，Spring boot 3.5.10、jdk17、Spring AI 1.1.2 也可以跑通demo，不过不知道有没有更多的坑
yml配置
server:port:8080spring:application:name: pocketmind-server ai:chat:client:observations:log-prompt:truelog-completion:trueopenai:api-key: xxxx # 替换为你的 API Key base-url: xxxx # 替换为你的 Base URL 不需要 /v1 chat: options:model: deepseek-chat # 替换为你使用的模型名称 示例demo采用 openai兼容的 api，如需兼容anthropic，那么根据对应文档进行切换即可
示例代码
skill.md
在根目录下添加对应的skill，skill的格式应该如下：
my-skill/ ├── SKILL.md # Required: instructions + metadata ├── scripts/ # Optional: executable code ├── references/ # Optional: documentation └── assets/ # Optional: templates, resources 在 skill.md 中 格式应该如下，至少应该包含元信息和详细的说明文档
--- name: code-reviewer description: Reviews Java code for best practices, security issues, and Spring Framework conventions. Use when user asks to review, analyze, or audit code --- # Code Reviewer ## Instructions When reviewing code: 1. Check **for** security vulnerabilities (SQL injection, XSS, etc.) 2. Verify Spring Boot best practices (proper use of @Service, @Repository, etc.) 3. Look **for** potential null pointer exceptions 4. Suggest improvements **for** readability and maintainability 5. Provide specific line-by-line feedback with code examples 示例如下：
controller
importorg.springaicommunity.agent.tools.FileSystemTools;importorg.springaicommunity.agent.tools.ShellTools;importorg.springaicommunity.agent.tools.SkillsTool;importorg.springframework.ai.chat.client.ChatClient;importorg.springframework.web.bind.annotation.*;importjava.util.Map;@RestController@RequestMapping("/demo")publicclassSkillController{privatefinalChatClient chatClient;publicSkillController(ChatClient.Builder chatClientBuilder){this.chatClient = chatClientBuilder .defaultToolCallbacks(SkillsTool.builder().addSkillsDirectory(".claude/skills")//也可以使用下面这个//.addSkillsResource(resourceLoader.getResource("classpath:.claude/skills")).build()).defaultTools(FileSystemTools.builder().build()).defaultTools(ShellTools.builder().build()).defaultToolContext(Map.of("foo","bar")).build();}/** * 测试 skill 流程 * @param message 用户的输入 * @return */@PostMapping("/skill")publicStringchat(@RequestBodyString message){return chatClient.prompt().user(message).call().content();}}此时运行程序，访问对应的端口即可查看返回内容
代码解释
- 先声明一个
ChatClient,并且通过DI进行注入 - 通过
chatClientBuilder进行builder策略构建.defaultToolCallbacks(...)：给ChatClient一个“已经组装好”的工具包（包含代码逻辑 + JSON Schema 描述），此处即为注册 skill 功能.defaultTools()： 注册对应的系统工具名称，用于动态发现skill来进行使用.defaultToolContext(Map.of("foo", "bar"))添加工具上下文，防止报错.defaultToolContext(Map.of("foo", "bar"))这个是为了框架报错，需要添加一个map传入作为ToolContext，否则无法正常build，为框架缺陷
- 通过链条进行构建llm的request
.user(message)加载用户提示词.call()由框架内部发其请求.content()获取大模型返回的内容
源码分析
0. 设置目录：
publicclassSkillsTool{//...publicstaticclassBuilder{privateList<Skill> skills =newArrayList<>();privateString toolDescriptionTemplate = TOOL_DESCRIPTION_TEMPLATE;protectedBuilder(){}publicBuildertoolDescriptionTemplate(String template){this.toolDescriptionTemplate = template;returnthis;}publicBuilderaddSkillsResources(List<Resource> skillsRootPaths){for(Resource skillsRootPath : skillsRootPaths){this.addSkillsResource(skillsRootPath);}returnthis;}publicBuilderaddSkillsResource(Resource skillsRootPath){try{String path = skillsRootPath.getFile().toPath().toAbsolutePath().toString();this.addSkillsDirectory(path);}catch(IOException ex){thrownewRuntimeException("Failed to load skills from directory: "+ skillsRootPath, ex);}returnthis;}publicBuilderaddSkillsDirectory(String skillsRootDirectory){this.addSkillsDirectories(List.of(skillsRootDirectory));returnthis;}publicBuilderaddSkillsDirectories(List<String> skillsRootDirectories){for(String skillsRootDirectory : skillsRootDirectories){try{this.skills.addAll(skills(skillsRootDirectory));}catch(IOException ex){thrownewRuntimeException("Failed to load skills from directory: "+ skillsRootDirectory, ex);}}returnthis;}//...}//...}addSkillsResource、addSkillsDirectory添加 skill 的路径，支持多个
toolDescriptionTemplate: 添加 skill 描述说明
1. 加载 skill 元数据
这是加载器的入口。它会去你指定的文件夹里找 SKILL.md 文件。/** * Recursively finds all SKILL.md files in the given root directory and returns their * parsed contents. * @param rootDirectory the root directory to search for SKILL.md files * @return a list of SkillFile objects containing the path, front-matter, and content * of each SKILL.md file * @throws IOException if an I/O error occurs while reading the directory or files */privatestaticList<Skill>skills(String rootDirectory)throwsIOException{Path rootPath =Paths.get(rootDirectory);if(!Files.exists(rootPath)){thrownewIOException("Root directory does not exist: "+ rootDirectory);}if(!Files.isDirectory(rootPath)){thrownewIOException("Path is not a directory: "+ rootDirectory);}List<Skill> skillFiles =newArrayList<>();try(Stream<Path> paths =Files.walk(rootPath)){ paths.filter(Files::isRegularFile).filter(path -> path.getFileName().toString().equals("SKILL.md"))// 遍历目录.forEach(path ->{try{// 解析文件：分为 FrontMatter (元数据) 和 Content (正文)String markdown =Files.readString(path,StandardCharsets.UTF_8);MarkdownParser parser =newMarkdownParser(markdown); skillFiles.add(newSkill(path, parser.getFrontMatter(), parser.getContent()));}catch(IOException e){thrownewRuntimeException("Failed to read SKILL.md file: "+ path, e);}});}return skillFiles;}- FrontMatter (YAML头)：包含技能的名字（如
name: pdf）和描述。这部分会被提取出来，告诉 AI “我有这个技能”。 - Content (正文)：这是具体的 Prompt 指令（比如“处理 PDF 的步骤是：1. 转换文本… 2. 提取摘要…”）。
- t添加 skill 技能
publicToolCallbackbuild(){Assert.notEmpty(this.skills,"At least one skill must be configured");String skillsXml =this.skills.stream().map(s -> s.toXml()).collect(Collectors.joining("\n"));returnFunctionToolCallback.builder("Skill",newSkillsFunction(toSkillsMap(this.skills))).description(this.toolDescriptionTemplate.formatted(skillsXml)).inputType(SkillsInput.class).build();}- 此步骤会把扫描到的技能列表编织进工具的描述里。
- 当 AI 看到这个工具时，它的 Prompt 里会出现你定义过的 skill 列表，例如：
<skill><name>pdf</name><description>Extract text from PDF</description></skill><skill><name>git</name><description>Git version control</description></skill>
3. 调用skill
当 AI 决定调用 Skill("pdf") 时，实际上触发了这段逻辑：publicstaticclassSkillsFunctionimplementsFunction<SkillsInput,String>{privateMap<String,Skill> skillsMap;publicSkillsFunction(Map<String,Skill> skillsMap){this.skillsMap = skillsMap;}@OverridepublicStringapply(SkillsInput input){Skill skill =this.skillsMap.get(input.command());if(skill !=null){var skillBaseDirectory = skill.path().getParent().toString();return"Base directory for this skill: %s\n\n%s".formatted(skillBaseDirectory, skill.content());}return"Skill not found: "+ input.command();}}- 此时返回的是“路径”和“正文内容”，于是 AI 读到返回的文字后，会发现这是一份“Code Review 的操作指南”。
至此 skill 的机制已经完整实现了，ai 只需要根据返回的 Skill.md 就可以调用对应的说明或者reference/scripts 下面的技能。
如果读者对于spring ai 框架下 ai 怎么进行多次工具调用循环好奇，可以查看Spring ai下的工具调用以及循环调用。
