type FrontMatter struct {
    Name        string      `yaml:"name"`
    Description string      `yaml:"description"`
    Context     ContextMode `yaml:"context"`
    Agent       string      `yaml:"agent"`
    Model       string      `yaml:"model"`
}

const (
    ContextModeFork            ContextMode = "fork"              // 隔离上下文
    ContextModeForkWithContext ContextMode = "fork_with_context" // 复制历史消息
)

type Skill struct {
    FrontMatter
    Content       string
    BaseDirectory string
}

type Backend interface {
    List(ctx context.Context) ([]FrontMatter, error)
    Get(ctx context.Context, name string) (Skill, error)
}

type BackendFromFilesystemConfig struct {
    Backend filesystem.Backend
    BaseDir string
}

func NewBackendFromFilesystem(ctx context.Context, config *BackendFromFilesystemConfig) (Backend, error)

// AgentHubOptions contains options passed to AgentHub.Get when creating an agent for skill execution.
type AgentHubOptions struct {
    // Model is the resolved model instance when a skill specifies a "model" field in frontmatter.
    // nil means the skill did not specify a model override; implementations should use their default.
    Model model.ToolCallingChatModel
}

// AgentHub provides agent instances for context mode (fork/fork_with_context) execution.
type AgentHub interface {
    // Get returns an Agent by name. When name is empty, implementations should return a default agent.
    // The opts parameter carries skill-level overrides (e.g., model) resolved by the framework.
    Get(ctx context.Context, name string, opts *AgentHubOptions) (adk.Agent, error)
}

// ModelHub 提供模型实例
type ModelHub interface {
    Get(ctx context.Context, name string) (model.ToolCallingChatModel, error)
}

func NewMiddleware(ctx context.Context, config *Config) (adk.ChatModelAgentMiddleware, error)

type Config struct {
    // Backend 技能后端实现，必填
    Backend Backend
    
    // SkillToolName 技能工具名称，默认 "skill"
    SkillToolName *string
    
    // AgentHub 提供 Agent 工厂函数，用于 Context 模式
    // 当 Skill 使用 "context: fork" 或 "context: isolate" 时必填
    AgentHub AgentHub
    
    // ModelHub 提供模型实例，用于 Skill 指定模型
    ModelHub ModelHub
    
    // CustomSystemPrompt 自定义系统提示词
    CustomSystemPrompt SystemPromptFunc
    
    // CustomToolDescription 自定义工具描述
    CustomToolDescription ToolDescriptionFunc
}

workdir/
├── skills/
│   └── pdf/
│        ├── scripts
│        │   └── analyze.py
│        └── SKILL.md
└── other files

import (
    "github.com/cloudwego/eino/adk/middlewares/skill"
    "github.com/cloudwego/eino-ext/adk/backend/local"
)

ctx := context.Background() 

be, err := local.NewBackend(ctx, &local.Config{})
if err != nil {
    log.Fatal(err)
}

skillBackend, err := skill.NewBackendFromFilesystem(ctx, &skill.BackendFromFilesystemConfig{
    Backend: be,
    BaseDir: skillsDir,
})
if err != nil {
    log.Fatalf("Failed to create skill backend: %v", err)
}

sm, err := skill.NewMiddleware(ctx, &skill.Config{
    Backend: skillBackend,
})

import (
    "github.com/cloudwego/eino/adk/middlewares/filesystem"
)

fsm, err := filesystem.New(ctx, &filesystem.MiddlewareConfig{
    Backend:        be,
    StreamingShell: be,
})

agent, err := adk.NewChatModelAgent(ctx, &adk.ChatModelAgentConfig{
    Name:        "LogAnalysisAgent",
    Description: "An agent that can analyze logs",
    Instruction: "You are a helpful assistant.",
    Model:       cm,
    Handlers:    []adk.ChatModelAgentMiddleware{fsm, sm},
})

runner := adk.NewRunner(ctx, adk.RunnerConfig{
    Agent: agent,
})

input := fmt.Sprintf("Analyze the %s file", filepath.Join(workDir, "test.log"))
log.Println("User: ", input)

iterator := runner.Query(ctx, input)
for {
    event, ok := iterator.Next()
    if !ok {
       break
    }
    if event.Err != nil {
       log.Printf("Error: %v\n", event.Err)
       break
    }

    prints.Event(event)
}

name: LogAnalysisAgent
path: [{LogAnalysisAgent}]
tool name: skill
arguments: {"skill":"log_analyzer"}

name: LogAnalysisAgent
path: [{LogAnalysisAgent}]
tool response: Launching skill: log_analyzer
Base directory for this skill: /Users/bytedance/go/src/github.com/cloudwego/eino-examples/adk/middlewares/skill/workdir/skills/log_analyzer
# SKILL.md content

name: LogAnalysisAgent
path: [{LogAnalysisAgent}]
tool name: execute
arguments:  {"command": "python3 /Users/bytedance/go/src/github.com/cloudwego/eino-examples/adk/middlewares/skill/workdir/skills/log_analyzer/scripts/analyze.py /Users/bytedance/go/src/github.com/cloudwego/eino-examples/adk/middlewares/skill/workdir/test.log"}

name: LogAnalysisAgent
path: [{LogAnalysisAgent}]
tool response: Analysis Result for /Users/bytedance/go/src/github.com/cloudwego/eino-examples/adk/middlewares/skill/workdir/test.log:
Total Errors: 2
Total Warnings: 1

Error Details:
Line 3: [2024-05-20 10:02:15] ERROR: Database connection failed.
Line 5: [2024-05-20 10:03:05] ERROR: Connection timed out.

Warning Details:
Line 2: [2024-05-20 10:01:23] WARNING: High memory usage detected.


name: LogAnalysisAgent
path: [{LogAnalysisAgent}]
answer: Here's the analysis result of the log file:

### Summary
- **Total Errors**: 2  
- **Total Warnings**: 1  

### Detailed Entries
#### Errors:
1. Line 3: [2024-05-20 10:02:15] ERROR: Database connection failed.  
2. Line5: [2024-05-2010:03:05] ERROR: Connection timed out.  

#### Warnings:
1. Line2: [2024-05-2010:01:23] WARNING: High memory usage detected.  

The log file contains critical issues related to database connectivity and a warning about memory usage. Let me know if you need further analysis!

# Skills System

**How to Use Skills (Progressive Disclosure):**

Skills follow a **progressive disclosure** pattern - you see their name and description above, but only read full instructions when needed:

1. **Recognize when a skill applies**: Check if the user's task matches a skill's description
2. **Read the skill's full instructions**: Use the '{tool_name}' tool to load skill
3. **Follow the skill's instructions**: tool result contains step-by-step workflows, best practices, and examples
4. **Access supporting files**: Skills may include helper scripts, configs, or reference docs - use absolute paths

**When to Use Skills:**
- User's request matches a skill's domain (e.g., "research X" -> web-research skill)
- You need specialized knowledge or structured workflows
- A skill provides proven patterns for complex tasks

**Executing Skill Scripts:**
Skills may contain Python scripts or other executable files. Always use absolute paths.

**Example Workflow:**

User: "Can you research the latest developments in quantum computing?"

1. Check available skills -> See "web-research" skill
2. Call '{tool_name}' tool to read the full skill instructions
3. Follow the skill's research workflow (search -> organize -> synthesize)
4. Use any helper scripts with absolute paths

Remember: Skills make you more capable and consistent. When in doubt, check if a skill exists for the task!

Execute a skill within the main conversation

<skills_instructions>
When users ask you to perform tasks, check if any of the available skills below can help complete the task more effectively. Skills provide specialized capabilities and domain knowledge.

How to invoke:
- Use this tool with the skill name only (no arguments)
- Examples:
  - `skill: pdf` - invoke the pdf skill
  - `skill: xlsx` - invoke the xlsx skill
  - `skill: ms-office-suite:pdf` - invoke using fully qualified name

Important:
- When a skill is relevant, you must invoke this tool IMMEDIATELY as your first action
- NEVER just announce or mention a skill in your text response without actually calling this tool
- This is a BLOCKING REQUIREMENT: invoke the relevant Skill tool BEFORE generating any other response about the task
- Only use skills listed in <available_skills> below
- Do not invoke a skill that is already running
- Do not use this tool for built-in CLI commands (like /help, /clear, etc.)
</skills_instructions>

<available_skills>
{{- range .Matters }}
<skill>
<name>
{{ .Name }}
</name>
<description>
{{ .Description }}
</description>
</skill>
{{- end }}
</available_skills>