a3s_code_core/tools/

skill.rs

//! Skill Tool - Invoke skills as callable tools with temporary permission grants
//!
//! This tool allows agents to invoke skills as first-class tools, with the skill's
//! allowed-tools temporarily granted during execution. This enforces skill-based
//! access patterns and prevents agents from bypassing skills to directly access
//! underlying tools.
//!
//! ## Usage
//!
//! ```text
//! // Agent calls: Skill("data-processor")
//! // The skill's allowed-tools are temporarily granted
//! // After execution, permissions are restored
//! ```

use crate::agent::{AgentConfig, AgentLoop};
use crate::llm::LlmClient;
use crate::permissions::{PermissionDecision, PermissionPolicy, PermissionRule};
use crate::skills::{Skill, SkillRegistry};
use crate::tools::{Tool, ToolContext, ToolExecutor, ToolOutput};
use anyhow::{anyhow, Result};
use async_trait::async_trait;
use serde::{Deserialize, Serialize};
use serde_json::Value;
use std::sync::{Arc, Weak};

/// Arguments for the Skill tool
#[derive(Debug, Serialize, Deserialize)]
pub struct SkillArgs {
    /// Name of the skill to invoke
    pub skill_name: String,
    /// Optional prompt/query to pass to the skill
    #[serde(default)]
    pub prompt: Option<String>,
}

impl SkillArgs {
    fn from_tool_args(args: &Value) -> Result<Self> {
        fn parse_from_value(value: &Value) -> Option<SkillArgs> {
            match value {
                Value::String(skill_name) => Some(SkillArgs {
                    skill_name: skill_name.clone(),
                    prompt: None,
                }),
                Value::Object(map) => {
                    if let Some(skill_name) = map
                        .get("skill_name")
                        .or_else(|| map.get("skillName"))
                        .or_else(|| map.get("name"))
                        .and_then(|v| v.as_str())
                    {
                        let prompt = map
                            .get("prompt")
                            .or_else(|| map.get("query"))
                            .and_then(|v| v.as_str())
                            .map(ToOwned::to_owned);
                        return Some(SkillArgs {
                            skill_name: skill_name.to_string(),
                            prompt,
                        });
                    }

                    if let Some(nested) = map.get("input").or_else(|| map.get("arguments")) {
                        if let Some(parsed) = parse_from_value(nested) {
                            return Some(parsed);
                        }
                    }

                    None
                }
                _ => None,
            }
        }

        parse_from_value(args).ok_or_else(|| anyhow!("missing field 'skill_name'"))
    }
}

/// Arguments for the search_skills tool
#[derive(Debug, Serialize, Deserialize)]
pub struct SearchSkillsArgs {
    /// Query describing the desired skill
    pub query: String,
    /// Maximum number of results to return
    #[serde(default)]
    pub limit: Option<usize>,
}

impl SearchSkillsArgs {
    fn from_tool_args(args: &Value) -> Result<Self> {
        match args {
            Value::String(query) => Ok(Self {
                query: query.clone(),
                limit: None,
            }),
            Value::Object(map) => {
                let query = map
                    .get("query")
                    .or_else(|| map.get("q"))
                    .and_then(|v| v.as_str())
                    .ok_or_else(|| anyhow!("missing field 'query'"))?
                    .to_string();
                let limit = map
                    .get("limit")
                    .and_then(|v| v.as_u64())
                    .map(|v| v as usize);
                Ok(Self { query, limit })
            }
            _ => Err(anyhow!(
                "search_skills expects an object with a 'query' field"
            )),
        }
    }
}

/// Search available skills without injecting all skill descriptions into context.
pub struct SearchSkillsTool {
    skill_registry: Arc<SkillRegistry>,
}

impl SearchSkillsTool {
    pub fn new(skill_registry: Arc<SkillRegistry>) -> Self {
        Self { skill_registry }
    }
}

#[async_trait]
impl Tool for SearchSkillsTool {
    fn name(&self) -> &str {
        "search_skills"
    }

    fn description(&self) -> &str {
        "Search available skills by name, tag, description, or content. \
Use this before invoking Skill when specialized instructions may help."
    }

    fn parameters(&self) -> Value {
        serde_json::json!({
            "type": "object",
            "additionalProperties": false,
            "properties": {
                "query": {
                    "type": "string",
                    "description": "Short search query for the skill you need."
                },
                "limit": {
                    "type": "integer",
                    "minimum": 1,
                    "maximum": 20,
                    "description": "Maximum number of skills to return. Defaults to 5."
                }
            },
            "required": ["query"]
        })
    }

    async fn execute(&self, args: &Value, _ctx: &ToolContext) -> Result<ToolOutput> {
        let args = SearchSkillsArgs::from_tool_args(args)?;
        let limit = args.limit.unwrap_or(5).clamp(1, 20);
        let matches = self.skill_registry.search(&args.query, limit);

        if matches.is_empty() {
            return Ok(ToolOutput::success(
                "No matching skills found. Continue with the core tools.".to_string(),
            ));
        }

        let mut lines = vec![format!(
            "Found {} matching skill(s). Invoke one with Skill using its skill_name.",
            matches.len()
        )];
        let metadata: Vec<_> = matches
            .iter()
            .map(|skill| {
                let kind = format!("{:?}", skill.kind).to_lowercase();
                let allowed_tools = skill.allowed_tools.as_deref().unwrap_or("not specified");
                lines.push(format!(
                    "- {} ({kind}): {} Allowed tools: {}.",
                    skill.name, skill.description, allowed_tools
                ));
                serde_json::json!({
                    "name": skill.name,
                    "description": skill.description,
                    "kind": kind,
                    "tags": skill.tags,
                    "allowed_tools": skill.allowed_tools,
                })
            })
            .collect();

        Ok(ToolOutput {
            content: lines.join("\n"),
            success: true,
            metadata: Some(serde_json::json!({ "skills": metadata })),
            images: Vec::new(),
            error_kind: None,
        })
    }
}

/// Skill tool - invokes skills with temporary permission grants
pub struct SkillTool {
    skill_registry: Arc<SkillRegistry>,
    llm_client: Arc<dyn LlmClient>,
    tool_executor: SkillToolExecutor,
    base_config: AgentConfig,
}

enum SkillToolExecutor {
    #[cfg(test)]
    Standalone(Arc<ToolExecutor>),
    RegistryBound(Weak<ToolExecutor>),
}

impl SkillToolExecutor {
    fn resolve(&self) -> Option<Arc<ToolExecutor>> {
        match self {
            #[cfg(test)]
            Self::Standalone(executor) => Some(executor.clone()),
            Self::RegistryBound(executor) => executor.upgrade(),
        }
    }
}

impl SkillTool {
    #[cfg(test)]
    pub(crate) fn new(
        skill_registry: Arc<SkillRegistry>,
        llm_client: Arc<dyn LlmClient>,
        tool_executor: Arc<ToolExecutor>,
        base_config: AgentConfig,
    ) -> Self {
        Self {
            skill_registry,
            llm_client,
            tool_executor: SkillToolExecutor::Standalone(tool_executor),
            base_config,
        }
    }

    /// Construct the Skill tool installed inside the supplied executor's own
    /// registry. The back-reference must be weak or registration would create
    /// an executor-registry-tool ownership cycle.
    pub(crate) fn new_registry_bound(
        skill_registry: Arc<SkillRegistry>,
        llm_client: Arc<dyn LlmClient>,
        tool_executor: Arc<ToolExecutor>,
        base_config: AgentConfig,
    ) -> Self {
        Self {
            skill_registry,
            llm_client,
            tool_executor: SkillToolExecutor::RegistryBound(Arc::downgrade(&tool_executor)),
            base_config,
        }
    }

    /// Create a temporary permission policy that grants the skill's allowed-tools
    fn create_skill_permission_policy(skill: &Skill) -> PermissionPolicy {
        let permissions = skill.parse_allowed_tools();

        if permissions.is_empty() {
            tracing::warn!(
                skill = %skill.name,
                "Skill has no allowed-tools grants; Skill invocation remains fail-secure and will deny tool use"
            );
            return PermissionPolicy {
                deny: Vec::new(),
                allow: Vec::new(),
                ask: Vec::new(),
                default_decision: PermissionDecision::Deny,
                enabled: true,
            };
        }

        // Convert skill permissions to PermissionRules
        let mut allow_rules = Vec::new();
        for perm in permissions {
            // Create a rule string in the format "Tool(pattern)"
            let rule_str = if perm.pattern == "*" {
                perm.tool.clone()
            } else {
                format!("{}({})", perm.tool, perm.pattern)
            };
            allow_rules.push(PermissionRule::new(&rule_str));
        }

        PermissionPolicy {
            deny: Vec::new(),
            allow: allow_rules,
            ask: Vec::new(),
            default_decision: PermissionDecision::Deny, // Deny by default - only allow what skill specifies
            enabled: true,
        }
    }
}

#[async_trait]
impl Tool for SkillTool {
    fn name(&self) -> &str {
        "Skill"
    }

    fn description(&self) -> &str {
        "Invoke a skill with temporary permission grants. \
Use a JSON object with the canonical shape {\"skill_name\":\"<skill-name>\",\"prompt\":\"<optional prompt>\"}. \
Always send the skill name in the 'skill_name' field. Do not use aliases such as 'name' or 'skillName', and do not wrap the payload in 'input' or 'arguments'. \
The skill's allowed-tools are granted during execution and revoked after completion."
    }

    fn parameters(&self) -> Value {
        serde_json::json!({
            "type": "object",
            "additionalProperties": false,
            "properties": {
                "skill_name": {
                    "type": "string",
                    "description": "Required. Canonical skill identifier to invoke. Always provide this exact field name: 'skill_name'."
                },
                "prompt": {
                    "type": "string",
                    "description": "Optional prompt or query to pass to the skill after it is loaded."
                }
            },
            "required": ["skill_name"],
            "examples": [
                {
                    "skill_name": "code-review"
                },
                {
                    "skill_name": "code-review",
                    "prompt": "Review this patch for correctness and regressions."
                }
            ]
        })
    }

    async fn execute(&self, args: &Value, ctx: &ToolContext) -> Result<ToolOutput> {
        let args = SkillArgs::from_tool_args(args)?;

        // Get the skill
        let skill = self
            .skill_registry
            .get(&args.skill_name)
            .ok_or_else(|| anyhow!("Skill '{}' not found", args.skill_name))?;

        // Create temporary permission policy with skill's allowed-tools
        let skill_permission_policy = Self::create_skill_permission_policy(&skill);

        // Create a modified config with the skill's permissions
        let mut skill_config = self.base_config.clone();
        if ctx.has_run_governance() {
            skill_config.permission_checker = ctx.run_permission_checker();
            skill_config.confirmation_manager = ctx.run_confirmation_manager();
        }

        // A skill narrows the tools it may use; it must not replace the host
        // boundary. Compose both checkers so TUI mode decisions, sandbox
        // availability, and explicit escalation denials remain authoritative
        // inside the skill child run.
        let parent_checker = skill_config.permission_checker.take();
        let parent_policy = skill_config.permission_policy.clone();
        skill_config.permission_checker = Some(crate::child_run::compose_permission_checker(
            Arc::new(skill_permission_policy.clone()),
            Some(skill_permission_policy.clone()),
            parent_checker,
            parent_policy,
        ));
        skill_config.permission_policy = Some(skill_permission_policy);
        skill_config.enforce_active_skill_tool_restrictions = true;

        // Create a temporary skill registry with only this skill
        let temp_registry = Arc::new(SkillRegistry::new());
        temp_registry.register(skill.clone())?;
        skill_config.skill_registry = Some(temp_registry);

        // Build the system prompt with skill content
        skill_config.prompt_slots.role = Some(format!(
            "You are executing the '{}' skill.\n\n{}\n\n{}",
            skill.name, skill.description, skill.content
        ));

        let capability_subtask = ctx
            .capability_context()
            .map(|context| context.admit_subtask(format!("skill-{}", uuid::Uuid::new_v4()), false))
            .transpose()?;
        let cancellation = capability_subtask.as_ref().map_or_else(
            || ctx.cancellation_token(),
            crate::capability::AgentCapabilitySubtask::cancellation,
        );

        // Create the child Agent loop inside the Skill's spatial Subtask. Its
        // provider/tool iterations will recursively create temporal Turns.
        let tool_executor = self
            .tool_executor
            .resolve()
            .ok_or_else(|| anyhow!("Skill tool executor is closed"))?;
        let mut agent_loop = AgentLoop::new(
            self.llm_client.clone(),
            tool_executor,
            ctx.clone(),
            skill_config,
        );
        if let Some(subtask) = capability_subtask.as_ref() {
            agent_loop = agent_loop.with_capability_runtime(subtask.runtime());
        }

        // Execute the skill with the prompt
        let prompt = args
            .prompt
            .unwrap_or_else(|| format!("Execute the '{}' skill", skill.name));

        // The skill remains inside the owning Run's cancellation and budget
        // scope. Its Subtask token is derived from the invoking Turn, so parent
        // cancellation reaches every provider/tool call without allowing the
        // child to cancel its parent.
        let execution = agent_loop
            .execute_with_session(
                &[],
                &prompt,
                ctx.session_id.as_deref(),
                None,
                Some(&cancellation),
            )
            .await;
        let cancelled = cancellation.is_cancelled();
        let close = close_skill_capability_subtask(capability_subtask.as_ref()).await;
        let result = match (execution, close) {
            (Ok(result), Ok(())) => result,
            (Ok(_), Err(close_error)) => return Err(close_error),
            (Err(error), Ok(())) => return Err(error),
            (Err(error), Err(close_error)) => {
                tracing::warn!(
                    error = %close_error,
                    "Capability Skill Subtask close also failed after execution failure"
                );
                return Err(error);
            }
        };
        if cancelled {
            anyhow::bail!("Skill '{}' cancelled by caller", skill.name);
        }

        // Return the final response as tool output
        Ok(ToolOutput {
            content: result.text,
            success: true,
            metadata: Some(serde_json::json!({
                "skill_name": skill.name,
                "tool_calls": result.tool_calls_count,
                "usage": result.usage,
            })),
            images: Vec::new(),
            error_kind: None,
        })
    }
}

async fn close_skill_capability_subtask(
    subtask: Option<&crate::capability::AgentCapabilitySubtask>,
) -> Result<()> {
    let Some(subtask) = subtask else {
        return Ok(());
    };
    let report = subtask.close().await?;
    if !report.is_clean() {
        anyhow::bail!(
            "Capability Skill Subtask close was incomplete (tasks failed: {}, tasks timed out: {}, child scopes failed: {}, child scopes timed out: {}, effects failed: {}, effects timed out: {})",
            report.tasks_failed,
            report.tasks_timed_out,
            report.child_scopes_failed,
            report.child_scopes_timed_out,
            report.effects_failed,
            report.effects_timed_out,
        );
    }
    Ok(())
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::budget::{BudgetDecision, BudgetGuard};
    use crate::llm::{
        ContentBlock, LlmClient, LlmResponse, Message, StreamEvent, TokenUsage, ToolDefinition,
    };
    use crate::skills::SkillKind;
    use crate::tools::ToolContext;
    use anyhow::Result;
    use async_trait::async_trait;
    use std::path::PathBuf;
    use std::sync::atomic::{AtomicUsize, Ordering};
    use std::sync::Mutex;
    use std::time::Duration;
    use tokio::sync::{mpsc, Notify};
    use tokio_util::sync::CancellationToken;

    struct MockLlmClient {
        responses: Mutex<Vec<LlmResponse>>,
    }

    impl MockLlmClient {
        fn new(responses: Vec<LlmResponse>) -> Self {
            Self {
                responses: Mutex::new(responses),
            }
        }

        fn text_response(text: &str) -> LlmResponse {
            LlmResponse {
                message: Message {
                    role: "assistant".to_string(),
                    content: vec![ContentBlock::Text {
                        text: text.to_string(),
                    }],
                    reasoning_content: None,
                },
                usage: TokenUsage {
                    prompt_tokens: 10,
                    completion_tokens: 5,
                    total_tokens: 15,
                    cache_read_tokens: None,
                    cache_write_tokens: None,
                },
                stop_reason: Some("end_turn".to_string()),
                token_logprobs: Vec::new(),
                meta: None,
            }
        }

        fn tool_call_response(id: &str, name: &str, input: serde_json::Value) -> LlmResponse {
            LlmResponse {
                message: Message {
                    role: "assistant".to_string(),
                    content: vec![ContentBlock::ToolUse {
                        id: id.to_string(),
                        name: name.to_string(),
                        input,
                    }],
                    reasoning_content: None,
                },
                usage: TokenUsage {
                    prompt_tokens: 10,
                    completion_tokens: 5,
                    total_tokens: 15,
                    cache_read_tokens: None,
                    cache_write_tokens: None,
                },
                stop_reason: Some("tool_use".to_string()),
                token_logprobs: Vec::new(),
                meta: None,
            }
        }
    }

    #[async_trait]
    impl LlmClient for MockLlmClient {
        async fn complete(
            &self,
            _messages: &[Message],
            _system: Option<&str>,
            _tools: &[ToolDefinition],
        ) -> Result<LlmResponse> {
            let mut responses = self.responses.lock().unwrap();
            if responses.is_empty() {
                anyhow::bail!("No more mock responses available");
            }
            Ok(responses.remove(0))
        }

        async fn complete_streaming(
            &self,
            _messages: &[Message],
            _system: Option<&str>,
            _tools: &[ToolDefinition],
            _cancel_token: tokio_util::sync::CancellationToken,
        ) -> Result<mpsc::Receiver<StreamEvent>> {
            anyhow::bail!("streaming not used in SkillTool tests")
        }
    }

    #[test]
    fn skill_tool_does_not_retain_its_executor() {
        let executor = Arc::new(ToolExecutor::new("skill-cycle-test".to_string()));
        let lifetime = Arc::downgrade(&executor);
        let _tool = SkillTool::new_registry_bound(
            Arc::new(SkillRegistry::new()),
            Arc::new(MockLlmClient::new(Vec::new())),
            executor.clone(),
            AgentConfig::default(),
        );

        drop(executor);

        assert!(lifetime.upgrade().is_none());
    }

    #[derive(Default)]
    struct SkillBudgetGuard {
        checks: AtomicUsize,
        records: AtomicUsize,
        sessions: Mutex<Vec<String>>,
    }

    #[async_trait]
    impl BudgetGuard for SkillBudgetGuard {
        async fn check_before_llm(
            &self,
            session_id: &str,
            _estimated_prompt_tokens: usize,
        ) -> BudgetDecision {
            self.checks.fetch_add(1, Ordering::SeqCst);
            self.sessions.lock().unwrap().push(session_id.to_string());
            BudgetDecision::Allow
        }

        async fn record_after_llm(&self, _session_id: &str, _usage: &TokenUsage) {
            self.records.fetch_add(1, Ordering::SeqCst);
        }
    }

    struct BlockingSkillClient {
        started: Arc<Notify>,
        calls: Arc<AtomicUsize>,
    }

    struct SkillSideEffectTool {
        calls: Arc<AtomicUsize>,
    }

    struct SkillScopeProbeTool {
        log: Arc<Mutex<Vec<String>>>,
    }

    struct SkillScopeProbeEffect {
        scope_id: String,
        log: Arc<Mutex<Vec<String>>>,
    }

    #[async_trait]
    impl crate::capability::CapabilityEffect for SkillScopeProbeEffect {
        fn name(&self) -> &str {
            "test.skill.scope.effect"
        }

        async fn close(
            self: Box<Self>,
        ) -> std::result::Result<(), crate::capability::CapabilityEffectError> {
            self.log
                .lock()
                .unwrap()
                .push(format!("closed:{}", self.scope_id));
            Ok(())
        }
    }

    #[async_trait]
    impl Tool for SkillScopeProbeTool {
        fn name(&self) -> &str {
            "skill_scope_probe"
        }

        fn description(&self) -> &str {
            "Records the capability Turn owned by a nested Skill Agent"
        }

        fn parameters(&self) -> serde_json::Value {
            serde_json::json!({"type": "object", "additionalProperties": false})
        }

        fn capabilities(&self, _args: &serde_json::Value) -> crate::tools::ToolCapabilities {
            crate::tools::ToolCapabilities::parallel_safe_read(1)
        }

        async fn execute(
            &self,
            _args: &serde_json::Value,
            ctx: &ToolContext,
        ) -> Result<ToolOutput> {
            let scope_id = ctx
                .capability_scope_id()
                .ok_or_else(|| anyhow!("nested Skill Tool has no capability Turn"))?
                .to_owned();
            self.log
                .lock()
                .unwrap()
                .push(format!("registered:{scope_id}"));
            ctx.register_capability_effect(SkillScopeProbeEffect {
                scope_id,
                log: Arc::clone(&self.log),
            })?;
            Ok(ToolOutput::success("registered"))
        }
    }

    #[async_trait]
    impl Tool for SkillSideEffectTool {
        fn name(&self) -> &str {
            "side_effect"
        }

        fn description(&self) -> &str {
            "Records a test-only side effect"
        }

        fn parameters(&self) -> serde_json::Value {
            serde_json::json!({"type": "object", "additionalProperties": false})
        }

        async fn execute(
            &self,
            _args: &serde_json::Value,
            _ctx: &ToolContext,
        ) -> Result<ToolOutput> {
            self.calls.fetch_add(1, Ordering::SeqCst);
            Ok(ToolOutput::success("unexpected-side-effect"))
        }
    }

    #[async_trait]
    impl LlmClient for BlockingSkillClient {
        async fn complete(
            &self,
            _messages: &[Message],
            _system: Option<&str>,
            _tools: &[ToolDefinition],
        ) -> Result<LlmResponse> {
            self.calls.fetch_add(1, Ordering::SeqCst);
            self.started.notify_one();
            std::future::pending::<Result<LlmResponse>>().await
        }

        async fn complete_streaming(
            &self,
            _messages: &[Message],
            _system: Option<&str>,
            _tools: &[ToolDefinition],
            _cancel_token: CancellationToken,
        ) -> Result<mpsc::Receiver<StreamEvent>> {
            anyhow::bail!("streaming not used in SkillTool cancellation tests")
        }
    }

    fn test_skill_registry() -> Arc<SkillRegistry> {
        let registry = Arc::new(SkillRegistry::new());
        registry.register_unchecked(Arc::new(Skill {
            name: "test-skill".to_string(),
            description: "Run a focused skill".to_string(),
            allowed_tools: None,
            disable_model_invocation: false,
            kind: SkillKind::Instruction,
            content: "Reply with the skill result.".to_string(),
            tags: vec!["focus".to_string()],
            version: None,
        }));
        registry
    }

    #[test]
    fn test_skill_permission_policy() {
        let skill = Skill {
            name: "test-skill".to_string(),
            description: "Test".to_string(),
            allowed_tools: Some("read(*), grep(*)".to_string()),
            disable_model_invocation: false,
            kind: SkillKind::Instruction,
            content: String::new(),
            tags: Vec::new(),
            version: None,
        };

        let policy = SkillTool::create_skill_permission_policy(&skill);

        // Should allow tools in allowed-tools
        assert_eq!(
            policy.check("read", &serde_json::json!({})),
            PermissionDecision::Allow
        );
        assert_eq!(
            policy.check(
                "search",
                &serde_json::json!({"mode": "grep", "query": "TODO"}),
            ),
            PermissionDecision::Allow
        );

        // Should deny tools not in allowed-tools
        assert_eq!(
            policy.check("write", &serde_json::json!({})),
            PermissionDecision::Deny
        );
    }

    #[test]
    fn test_skill_permission_policy_denies_when_unspecified() {
        let skill = Skill {
            name: "test-skill".to_string(),
            description: "Test".to_string(),
            allowed_tools: None,
            disable_model_invocation: false,
            kind: SkillKind::Instruction,
            content: String::new(),
            tags: Vec::new(),
            version: None,
        };

        let policy = SkillTool::create_skill_permission_policy(&skill);

        assert_eq!(
            policy.check("bash", &serde_json::json!({"command": "python --version"})),
            PermissionDecision::Deny
        );
        assert_eq!(
            policy.check("read", &serde_json::json!({"file_path": "SKILL.md"})),
            PermissionDecision::Deny
        );
    }

    #[test]
    fn test_skill_permission_policy_accepts_legacy_allowed_tools() {
        let skill = Skill {
            name: "test-skill".to_string(),
            description: "Test".to_string(),
            allowed_tools: Some("Read Write Edit Bash".to_string()),
            disable_model_invocation: false,
            kind: SkillKind::Instruction,
            content: String::new(),
            tags: Vec::new(),
            version: None,
        };

        let policy = SkillTool::create_skill_permission_policy(&skill);

        assert_eq!(
            policy.check("bash", &serde_json::json!({"command": "python --version"})),
            PermissionDecision::Allow
        );
        assert_eq!(
            policy.check("search", &serde_json::json!({"mode": "grep", "query": "x"}),),
            PermissionDecision::Deny
        );
    }

    #[test]
    fn test_skill_permission_policy_accepts_wildcard_allowed_tools() {
        let skill = Skill {
            name: "test-skill".to_string(),
            description: "Test".to_string(),
            allowed_tools: Some("*".to_string()),
            disable_model_invocation: false,
            kind: SkillKind::Instruction,
            content: String::new(),
            tags: Vec::new(),
            version: None,
        };

        let policy = SkillTool::create_skill_permission_policy(&skill);

        assert_eq!(
            policy.check("bash", &serde_json::json!({"command": "python --version"})),
            PermissionDecision::Allow
        );
        assert_eq!(
            policy.check("parallel_task", &serde_json::json!({"tasks": []})),
            PermissionDecision::Allow
        );
    }

    #[test]
    fn test_skill_args_accepts_documented_shape() {
        let args =
            SkillArgs::from_tool_args(&serde_json::json!({"skill_name": "code-review"})).unwrap();
        assert_eq!(args.skill_name, "code-review");
        assert_eq!(args.prompt, None);
    }

    #[test]
    fn test_skill_args_accepts_common_aliases_and_wrappers() {
        let camel =
            SkillArgs::from_tool_args(&serde_json::json!({"skillName": "code-review"})).unwrap();
        assert_eq!(camel.skill_name, "code-review");

        let name = SkillArgs::from_tool_args(&serde_json::json!({
            "name": "code-review",
            "query": "review this patch"
        }))
        .unwrap();
        assert_eq!(name.skill_name, "code-review");
        assert_eq!(name.prompt.as_deref(), Some("review this patch"));

        let nested = SkillArgs::from_tool_args(&serde_json::json!({
            "input": {
                "skill_name": "code-review",
                "prompt": "review this patch"
            }
        }))
        .unwrap();
        assert_eq!(nested.skill_name, "code-review");
        assert_eq!(nested.prompt.as_deref(), Some("review this patch"));

        let direct = SkillArgs::from_tool_args(&serde_json::json!("code-review")).unwrap();
        assert_eq!(direct.skill_name, "code-review");
    }

    #[test]
    fn test_skill_args_missing_skill_name_errors() {
        let err =
            SkillArgs::from_tool_args(&serde_json::json!({"prompt": "do something"})).unwrap_err();
        assert!(err.to_string().contains("missing field 'skill_name'"));
    }

    #[test]
    fn test_search_skills_args_accepts_string_and_object() {
        let direct = SearchSkillsArgs::from_tool_args(&serde_json::json!("review code")).unwrap();
        assert_eq!(direct.query, "review code");
        assert_eq!(direct.limit, None);

        let object =
            SearchSkillsArgs::from_tool_args(&serde_json::json!({"query": "review", "limit": 2}))
                .unwrap();
        assert_eq!(object.query, "review");
        assert_eq!(object.limit, Some(2));
    }

    #[tokio::test]
    async fn test_search_skills_tool_returns_matching_skills() {
        let registry = Arc::new(SkillRegistry::new());
        registry.register_unchecked(Arc::new(Skill {
            name: "code-review".to_string(),
            description: "Review code changes".to_string(),
            allowed_tools: Some("read(*), grep(*)".to_string()),
            disable_model_invocation: false,
            kind: SkillKind::Instruction,
            content: "Review instructions".to_string(),
            tags: vec!["review".to_string()],
            version: None,
        }));

        let tool = SearchSkillsTool::new(registry);
        let result = tool
            .execute(
                &serde_json::json!({"query": "review"}),
                &ToolContext::new(PathBuf::from("/tmp")),
            )
            .await
            .unwrap();

        assert!(result.success);
        assert!(result.content.contains("code-review"));
        assert_eq!(result.metadata.unwrap()["skills"][0]["name"], "code-review");
    }

    #[tokio::test]
    async fn test_search_skills_tool_clamps_limit_and_excludes_personas() {
        let registry = Arc::new(SkillRegistry::new());
        for index in 0..25 {
            registry.register_unchecked(Arc::new(Skill {
                name: format!("review-{index:02}"),
                description: "Review code changes".to_string(),
                allowed_tools: Some("read(*)".to_string()),
                disable_model_invocation: false,
                kind: SkillKind::Instruction,
                content: "Review instructions".to_string(),
                tags: vec!["review".to_string()],
                version: None,
            }));
        }
        registry.register_unchecked(Arc::new(Skill {
            name: "review-persona".to_string(),
            description: "Review persona".to_string(),
            allowed_tools: None,
            disable_model_invocation: false,
            kind: SkillKind::Persona,
            content: "Persona instructions".to_string(),
            tags: vec!["review".to_string()],
            version: None,
        }));

        let tool = SearchSkillsTool::new(registry);
        let result = tool
            .execute(
                &serde_json::json!({"query": "review", "limit": 100}),
                &ToolContext::new(PathBuf::from("/tmp")),
            )
            .await
            .unwrap();

        let metadata = result.metadata.unwrap();
        let skills = metadata["skills"].as_array().unwrap();
        assert_eq!(skills.len(), 20);
        assert!(skills.iter().all(|skill| skill["kind"] == "instruction"));
    }

    #[test]
    fn test_skill_tool_schema_enforces_canonical_shape() {
        let registry = Arc::new(SkillRegistry::new());
        let llm = Arc::new(MockLlmClient::new(vec![]));
        let executor = Arc::new(ToolExecutor::new("/tmp".to_string()));
        let tool = SkillTool::new(registry, llm, executor, AgentConfig::default());

        let params = tool.parameters();
        assert_eq!(params["type"], "object");
        assert_eq!(params["additionalProperties"], serde_json::json!(false));
        assert_eq!(params["required"], serde_json::json!(["skill_name"]));

        let examples = params["examples"].as_array().unwrap();
        assert_eq!(examples[0]["skill_name"], "code-review");
        assert!(examples[0].get("name").is_none());
        assert!(examples[0].get("skillName").is_none());
    }

    #[tokio::test]
    async fn test_skill_tool_execute_runs_skill_and_returns_metadata() {
        use crate::prompts::PlanningMode;

        let registry = Arc::new(SkillRegistry::new());
        registry.register_unchecked(Arc::new(Skill {
            name: "test-skill".to_string(),
            description: "Run a focused skill".to_string(),
            allowed_tools: None,
            disable_model_invocation: false,
            kind: SkillKind::Instruction,
            content: "Reply with the skill result.".to_string(),
            tags: vec!["focus".to_string()],
            version: None,
        }));

        let llm = Arc::new(MockLlmClient::new(vec![MockLlmClient::text_response(
            "skill completed",
        )]));
        let executor = Arc::new(ToolExecutor::new("/tmp".to_string()));
        // Disable planning mode since the mock only has one response
        let config = AgentConfig {
            planning_mode: PlanningMode::Disabled,
            continuation_enabled: false,
            ..Default::default()
        };
        let tool = SkillTool::new(registry, llm, executor, config);

        let result = tool
            .execute(
                &serde_json::json!({
                    "skill_name": "test-skill",
                    "prompt": "verify the skill result"
                }),
                &ToolContext::new(PathBuf::from("/tmp")),
            )
            .await
            .unwrap();

        assert!(result.success);
        assert_eq!(result.content, "skill completed");
        let metadata = result.metadata.unwrap();
        assert_eq!(metadata["skill_name"], "test-skill");
        assert_eq!(metadata["tool_calls"], 0);
    }

    #[tokio::test]
    async fn skill_child_agent_owns_recursive_subtask_and_turn_scopes() {
        use crate::prompts::PlanningMode;

        let workspace = tempfile::tempdir().unwrap();
        let registry = Arc::new(SkillRegistry::new());
        registry.register_unchecked(Arc::new(Skill {
            name: "scoped-skill".to_string(),
            description: "Exercise nested scope ownership".to_string(),
            allowed_tools: Some("skill_scope_probe".to_string()),
            disable_model_invocation: false,
            kind: SkillKind::Instruction,
            content: "Call skill_scope_probe once, then finish.".to_string(),
            tags: Vec::new(),
            version: None,
        }));
        let log = Arc::new(Mutex::new(Vec::new()));
        let executor = Arc::new(ToolExecutor::new(
            workspace.path().to_string_lossy().into_owned(),
        ));
        executor.register_dynamic_tool(Arc::new(SkillScopeProbeTool {
            log: Arc::clone(&log),
        }));
        let tool = SkillTool::new(
            registry,
            Arc::new(MockLlmClient::new(vec![
                MockLlmClient::tool_call_response(
                    "skill-probe",
                    "skill_scope_probe",
                    serde_json::json!({}),
                ),
                MockLlmClient::text_response("skill complete"),
            ])),
            executor,
            AgentConfig {
                planning_mode: PlanningMode::Disabled,
                continuation_enabled: false,
                ..Default::default()
            },
        );
        let set = crate::capability::CapabilitySet::empty().unwrap();
        let ceiling = crate::capability::CapabilityCeiling::all(
            &set,
            crate::capability::WorkspaceCapabilityCeiling::all(),
            crate::capability::GovernanceCapabilityCeiling::none_required(),
            crate::capability::CapabilityExecutionCeiling::new(
                4,
                2,
                Some(1_000),
                Some(1_000),
                Some(5_000),
            )
            .unwrap(),
        )
        .unwrap();
        let session =
            crate::capability::CapabilityScope::<crate::capability::Session>::new_session(
                "session-1",
                set,
                ceiling.clone(),
            )
            .unwrap();
        let run = session.admit_run("run-1", ceiling).unwrap();
        let runtime = crate::capability::AgentCapabilityRuntime::from_run(&run);
        let parent_turn = runtime.begin_turn(1).unwrap();
        let capability_context = parent_turn.tool_context();
        let parent_scope_id = capability_context.foreground_scope_id().to_owned();
        let context = ToolContext::new(workspace.path().to_path_buf())
            .with_cancellation(parent_turn.cancellation())
            .with_capability_context(capability_context);

        let result = tool
            .execute(&serde_json::json!({"skill_name": "scoped-skill"}), &context)
            .await
            .unwrap();

        assert!(result.success, "{}", result.content);
        let entries = log.lock().unwrap().clone();
        assert_eq!(entries.len(), 2, "{entries:?}");
        let registered = entries[0].strip_prefix("registered:").unwrap();
        let closed = entries[1].strip_prefix("closed:").unwrap();
        assert_eq!(registered, closed);
        assert!(
            registered.starts_with(&format!("{parent_scope_id}/subtask/skill-")),
            "{registered}"
        );
        assert!(registered.contains("/turn/turn-1-1"), "{registered}");

        parent_turn.close().await.unwrap();
        run.close().await.unwrap();
        session.close().await.unwrap();
    }

    #[tokio::test]
    async fn skill_permissions_cannot_replace_the_parent_host_boundary() {
        use crate::prompts::PlanningMode;

        let workspace = tempfile::tempdir().unwrap();
        let registry = Arc::new(SkillRegistry::new());
        registry.register_unchecked(Arc::new(Skill {
            name: "bash-skill".to_string(),
            description: "Attempt a shell call".to_string(),
            allowed_tools: Some("bash(*)".to_string()),
            disable_model_invocation: false,
            kind: SkillKind::Instruction,
            content: "Use Bash once.".to_string(),
            tags: Vec::new(),
            version: None,
        }));
        let llm = Arc::new(MockLlmClient::new(vec![
            MockLlmClient::tool_call_response(
                "bash-call",
                "bash",
                serde_json::json!({"command": "printf leaked > skill-boundary-leak"}),
            ),
            MockLlmClient::text_response("The host boundary rejected the call."),
        ]));
        let parent_policy = PermissionPolicy::new().deny("bash(*)");
        let config = AgentConfig {
            planning_mode: PlanningMode::Disabled,
            continuation_enabled: false,
            permission_checker: Some(Arc::new(parent_policy.clone())),
            permission_policy: Some(parent_policy),
            ..Default::default()
        };
        let tool = SkillTool::new(
            registry,
            llm,
            Arc::new(ToolExecutor::new(
                workspace.path().to_string_lossy().into_owned(),
            )),
            config,
        );

        let result = tool
            .execute(
                &serde_json::json!({"skill_name": "bash-skill"}),
                &ToolContext::new(workspace.path().to_path_buf()),
            )
            .await
            .unwrap();

        assert!(result.success, "{}", result.content);
        assert!(
            !workspace.path().join("skill-boundary-leak").exists(),
            "a skill-local allow-list must not bypass the parent host boundary"
        );
    }

    #[tokio::test]
    async fn host_direct_context_does_not_leak_into_skill_model_orchestrators() {
        use crate::prompts::PlanningMode;

        struct RecordingBoundary {
            checked: Arc<Mutex<Vec<String>>>,
        }

        impl crate::permissions::PermissionChecker for RecordingBoundary {
            fn check(&self, tool_name: &str, _args: &serde_json::Value) -> PermissionDecision {
                self.checked.lock().unwrap().push(tool_name.to_string());
                if tool_name == "side_effect" {
                    PermissionDecision::Deny
                } else {
                    PermissionDecision::Allow
                }
            }
        }

        let workspace = tempfile::tempdir().unwrap();
        let calls = Arc::new(AtomicUsize::new(0));
        let checked = Arc::new(Mutex::new(Vec::new()));
        let registry = Arc::new(SkillRegistry::new());
        registry.register_unchecked(Arc::new(Skill {
            name: "orchestrator-skill".to_string(),
            description: "Exercise governed orchestrators".to_string(),
            allowed_tools: Some("batch(*), program(*), side_effect(*)".to_string()),
            disable_model_invocation: false,
            kind: SkillKind::Instruction,
            content: "Run the requested orchestration.".to_string(),
            tags: Vec::new(),
            version: None,
        }));
        let llm = Arc::new(MockLlmClient::new(vec![
            MockLlmClient::tool_call_response(
                "model-batch",
                "batch",
                serde_json::json!({
                    "invocations": [{
                        "tool": "program",
                        "args": {
                            "type": "script",
                            "language": "javascript",
                            "source": "async function run(ctx) { return await ctx.tool('side_effect', {}); }",
                            "allowed_tools": ["side_effect"]
                        }
                    }]
                }),
            ),
            MockLlmClient::text_response("The boundary held."),
        ]));
        let executor = Arc::new(ToolExecutor::new(
            workspace.path().to_string_lossy().into_owned(),
        ));
        executor.register_dynamic_tool(Arc::new(SkillSideEffectTool {
            calls: Arc::clone(&calls),
        }));
        let tool = SkillTool::new(
            registry,
            llm,
            executor,
            AgentConfig {
                planning_mode: PlanningMode::Disabled,
                continuation_enabled: false,
                permission_checker: Some(Arc::new(RecordingBoundary {
                    checked: Arc::clone(&checked),
                })),
                ..Default::default()
            },
        );
        let context = ToolContext::new(workspace.path().to_path_buf())
            .with_host_direct_policy(crate::tools::HostDirectPolicy::TrustedControlPlane);

        let result = tool
            .execute(
                &serde_json::json!({"skill_name": "orchestrator-skill"}),
                &context,
            )
            .await
            .unwrap();

        assert!(result.success, "{}", result.content);
        assert_eq!(result.content, "The boundary held.");
        assert_eq!(calls.load(Ordering::SeqCst), 0);
        let checked = checked.lock().unwrap();
        for expected in ["batch", "program", "side_effect"] {
            assert!(
                checked.iter().any(|tool| tool == expected),
                "{expected} must cross the parent permission boundary: {checked:?}"
            );
        }
    }

    #[tokio::test]
    async fn skill_child_llm_call_uses_parent_session_budget_scope() {
        use crate::prompts::PlanningMode;

        let guard = Arc::new(SkillBudgetGuard::default());
        let config = AgentConfig {
            planning_mode: PlanningMode::Disabled,
            continuation_enabled: false,
            budget_guard: Some(Arc::clone(&guard) as Arc<dyn BudgetGuard>),
            ..Default::default()
        };
        let tool = SkillTool::new(
            test_skill_registry(),
            Arc::new(MockLlmClient::new(vec![MockLlmClient::text_response(
                "skill completed",
            )])),
            Arc::new(ToolExecutor::new("/tmp".to_string())),
            config,
        );
        let ctx = ToolContext::new(PathBuf::from("/tmp")).with_session_id("parent-session");

        let result = tool
            .execute(&serde_json::json!({"skill_name": "test-skill"}), &ctx)
            .await
            .unwrap();

        assert!(result.success);
        assert_eq!(guard.checks.load(Ordering::SeqCst), 1);
        assert_eq!(guard.records.load(Ordering::SeqCst), 1);
        assert_eq!(
            guard.sessions.lock().unwrap().as_slice(),
            &["parent-session".to_string()]
        );
    }

    #[tokio::test]
    async fn skill_child_llm_call_stops_on_parent_cancellation() {
        use crate::prompts::PlanningMode;

        let started = Arc::new(Notify::new());
        let calls = Arc::new(AtomicUsize::new(0));
        let tool = SkillTool::new(
            test_skill_registry(),
            Arc::new(BlockingSkillClient {
                started: Arc::clone(&started),
                calls: Arc::clone(&calls),
            }),
            Arc::new(ToolExecutor::new("/tmp".to_string())),
            AgentConfig {
                planning_mode: PlanningMode::Disabled,
                continuation_enabled: false,
                ..Default::default()
            },
        );
        let cancellation = CancellationToken::new();
        let ctx = ToolContext::new(PathBuf::from("/tmp"))
            .with_session_id("parent-session")
            .with_cancellation(cancellation.clone());
        let started_wait = started.notified();
        let run = tokio::spawn(async move {
            tool.execute(&serde_json::json!({"skill_name": "test-skill"}), &ctx)
                .await
        });

        tokio::time::timeout(Duration::from_secs(1), started_wait)
            .await
            .expect("skill provider call should start");
        cancellation.cancel();
        let error = tokio::time::timeout(Duration::from_secs(1), run)
            .await
            .expect("parent cancellation must stop the skill child")
            .expect("skill join should succeed")
            .expect_err("cancelled skill must not return success");

        assert!(error.to_string().contains("cancelled"));
        assert_eq!(calls.load(Ordering::SeqCst), 1);
    }

    #[tokio::test]
    async fn test_skill_tool_execute_errors_for_unknown_skill() {
        let llm = Arc::new(MockLlmClient::new(vec![MockLlmClient::text_response(
            "unused",
        )]));
        let executor = Arc::new(ToolExecutor::new("/tmp".to_string()));
        let tool = SkillTool::new(
            Arc::new(SkillRegistry::new()),
            llm,
            executor,
            AgentConfig::default(),
        );

        let err = tool
            .execute(
                &serde_json::json!({"skill_name": "missing-skill"}),
                &ToolContext::new(PathBuf::from("/tmp")),
            )
            .await
            .unwrap_err();

        assert!(err.to_string().contains("Skill 'missing-skill' not found"));
    }
}