zclaw_openfang/crates/zclaw-skills/src/skill.rs

//! Skill definition and types

use serde::{Deserialize, Serialize};
use serde_json::Value;
use std::pin::Pin;
use zclaw_types::{SkillId, Result};

/// Type-erased LLM completion interface.
///
/// Defined here (in zclaw-skills) to avoid a circular dependency on zclaw-runtime.
/// Implementations live in zclaw-kernel where both crates are available.
pub trait LlmCompleter: Send + Sync {
    /// Complete a simple prompt → response (no system prompt, no tools).
    fn complete(
        &self,
        prompt: &str,
    ) -> Pin<Box<dyn std::future::Future<Output = std::result::Result<String, String>> + Send + '_>>;
}

/// Skill manifest definition
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct SkillManifest {
    /// Unique skill identifier
    pub id: SkillId,
    /// Human-readable name
    pub name: String,
    /// Skill description
    pub description: String,
    /// Skill version
    pub version: String,
    /// Skill author
    #[serde(default)]
    pub author: Option<String>,
    /// Execution mode
    pub mode: SkillMode,
    /// Required capabilities
    #[serde(default)]
    pub capabilities: Vec<String>,
    /// Input schema (JSON Schema)
    #[serde(default)]
    pub input_schema: Option<Value>,
    /// Output schema (JSON Schema)
    #[serde(default)]
    pub output_schema: Option<Value>,
    /// Tags for categorization
    #[serde(default)]
    pub tags: Vec<String>,
    /// Category for skill grouping (e.g., "开发工程", "数据分析")
    /// If not specified, will be auto-detected from skill ID
    #[serde(default)]
    pub category: Option<String>,
    /// Trigger words for skill activation
    #[serde(default)]
    pub triggers: Vec<String>,
    /// Whether the skill is enabled
    #[serde(default = "default_enabled")]
    pub enabled: bool,
}

fn default_enabled() -> bool { true }

/// Skill execution mode
#[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq)]
#[serde(rename_all = "snake_case")]
pub enum SkillMode {
    /// Prompt-only skill (no code execution)
    PromptOnly,
    /// Python script execution
    Python,
    /// Shell command execution
    Shell,
    /// WebAssembly execution (requires 'wasm' feature flag, falls back to PromptOnly otherwise)
    Wasm,
    /// Native Rust execution (not yet implemented, falls back to PromptOnly)
    Native,
}

/// Skill execution context
#[derive(Clone)]
pub struct SkillContext {
    /// Agent ID executing the skill
    pub agent_id: String,
    /// Session ID for the execution
    pub session_id: String,
    /// Working directory for execution
    pub working_dir: Option<std::path::PathBuf>,
    /// Environment variables
    pub env: std::collections::HashMap<String, String>,
    /// Timeout in seconds
    pub timeout_secs: u64,
    /// Whether to allow network access
    pub network_allowed: bool,
    /// Whether to allow file system access
    pub file_access_allowed: bool,
    /// Optional LLM completer for skills that need AI generation (e.g. PromptOnly)
    pub llm: Option<std::sync::Arc<dyn LlmCompleter>>,
}

impl std::fmt::Debug for SkillContext {
    fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
        f.debug_struct("SkillContext")
            .field("agent_id", &self.agent_id)
            .field("session_id", &self.session_id)
            .field("working_dir", &self.working_dir)
            .field("timeout_secs", &self.timeout_secs)
            .field("network_allowed", &self.network_allowed)
            .field("file_access_allowed", &self.file_access_allowed)
            .field("llm", &self.llm.as_ref().map(|_| "Arc<dyn LlmCompleter>"))
            .finish()
    }
}

impl Default for SkillContext {
    fn default() -> Self {
        Self {
            agent_id: String::new(),
            session_id: String::new(),
            working_dir: None,
            env: std::collections::HashMap::new(),
            timeout_secs: 60,
            network_allowed: false,
            file_access_allowed: false,
            llm: None,
        }
    }
}

/// Skill execution result
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct SkillResult {
    /// Whether execution succeeded
    pub success: bool,
    /// Output data
    pub output: Value,
    /// Error message if failed
    #[serde(default)]
    pub error: Option<String>,
    /// Execution duration in milliseconds
    #[serde(default)]
    pub duration_ms: Option<u64>,
    /// Token usage if LLM was    #[serde(default)]
    pub tokens_used: Option<u32>,
}

impl SkillResult {
    pub fn success(output: Value) -> Self {
        Self {
            success: true,
            output,
            error: None,
            duration_ms: None,
            tokens_used: None,
        }
    }

    pub fn error(message: impl Into<String>) -> Self {
        Self {
            success: false,
            output: Value::Null,
            error: Some(message.into()),
            duration_ms: None,
            tokens_used: None,
        }
    }
}

/// Skill definition with execution logic
#[async_trait::async_trait]
pub trait Skill: Send + Sync {
    /// Get the skill manifest
    fn manifest(&self) -> &SkillManifest;

    /// Execute the skill with given input
    async fn execute(&self, context: &SkillContext, input: Value) -> Result<SkillResult>;

    /// Validate input against schema
    fn validate_input(&self, input: &Value) -> Result<()> {
        // Basic validation - can be overridden
        if input.is_null() {
            return Err(zclaw_types::ZclawError::InvalidInput("Input cannot be null".into()));
        }
        Ok(())
    }
}