fix(audit): 修复深度审计发现的 P0/P1 问题 (8项)
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基于 DEEP_AUDIT_REPORT.md 修复 2 CRITICAL + 4 HIGH + 1 MEDIUM 问题:

- C1: PromptOnly 技能集成 LLM 调用 — 定义 LlmCompleter trait,
  通过 LlmDriverAdapter 桥接 zclaw_runtime::LlmDriver,
  PromptOnlySkill.execute() 现在调用 LLM 生成内容
- C2: 反思引擎空记忆 bug — 新增 query_memories_for_reflection()
  从 VikingStorage 查询真实记忆传入 reflect()
- H7: Agent Store 接口适配 — KernelClient 添加 listClones/createClone/
  deleteClone/updateClone 方法,映射到 agent_* 命令
- H8: Hand 审批检查 — hand_execute 执行前检查 needs_approval,
  需审批返回 pending_approval 状态
- M1: 幽灵命令注册 — 注册 hand_get/hand_run_status/hand_run_list
  三个 Tauri 桩命令
- H1/H2: SpeechHand/TwitterHand 添加 demo 标签
- H5: 归档过时 VERIFICATION_REPORT

文档更新: DEEP_AUDIT_REPORT.md 标记修复状态,README.md 更新
关键指标和变更历史。整体完成度从 ~50% 提升至 ~58%。
This commit is contained in:
iven
2026-03-27 09:36:50 +08:00
parent eed347e1a6
commit a71c4138cc
14 changed files with 902 additions and 43 deletions

View File

@@ -9,7 +9,7 @@ use tracing::debug;
use crate::intelligence::identity::IdentityManagerState;
use crate::intelligence::heartbeat::HeartbeatEngineState;
use crate::intelligence::reflection::ReflectionEngineState;
use crate::intelligence::reflection::{MemoryEntryForAnalysis, ReflectionEngineState};
/// Run pre-conversation intelligence hooks
///
@@ -40,6 +40,7 @@ pub async fn pre_conversation_hook(
/// 2. Record conversation for reflection engine, trigger reflection if needed
pub async fn post_conversation_hook(
agent_id: &str,
_user_message: &str,
_heartbeat_state: &HeartbeatEngineState,
reflection_state: &ReflectionEngineState,
) {
@@ -48,7 +49,6 @@ pub async fn post_conversation_hook(
debug!("[intelligence_hooks] Recorded interaction for agent: {}", agent_id);
// Step 2: Record conversation for reflection
// tokio::sync::Mutex::lock() returns MutexGuard directly (panics on poison)
let mut engine = reflection_state.lock().await;
engine.record_conversation();
@@ -62,7 +62,17 @@ pub async fn post_conversation_hook(
"[intelligence_hooks] Reflection threshold reached for agent: {}",
agent_id
);
let reflection_result = engine.reflect(agent_id, &[]);
// Query actual memories from VikingStorage for reflection analysis
let memories = query_memories_for_reflection(agent_id).await
.unwrap_or_default();
debug!(
"[intelligence_hooks] Fetched {} memories for reflection",
memories.len()
);
let reflection_result = engine.reflect(agent_id, &memories);
debug!(
"[intelligence_hooks] Reflection completed: {} patterns, {} suggestions",
reflection_result.patterns.len(),
@@ -151,3 +161,38 @@ async fn build_identity_prompt(
Ok(prompt)
}
/// Query agent memories from VikingStorage and convert to MemoryEntryForAnalysis
/// for the reflection engine.
///
/// Fetches up to 50 recent memories scoped to the given agent, without token
/// truncation (unlike build_memory_context which is size-limited for prompts).
async fn query_memories_for_reflection(
agent_id: &str,
) -> Result<Vec<MemoryEntryForAnalysis>, String> {
let storage = crate::viking_commands::get_storage().await?;
let options = zclaw_growth::FindOptions {
scope: Some(format!("agent://{}", agent_id)),
limit: Some(50),
min_similarity: Some(0.0), // Fetch all, no similarity filter
};
let results: Vec<zclaw_growth::MemoryEntry> =
zclaw_growth::VikingStorage::find(storage.as_ref(), "", options)
.await
.map_err(|e| format!("Memory query for reflection failed: {}", e))?;
let memories: Vec<MemoryEntryForAnalysis> = results
.into_iter()
.map(|entry| MemoryEntryForAnalysis {
memory_type: entry.memory_type.to_string(),
content: entry.content,
importance: entry.importance as usize,
access_count: entry.access_count as usize,
tags: entry.keywords,
})
.collect();
Ok(memories)
}

View File

@@ -450,7 +450,7 @@ pub async fn agent_chat_stream(
// Start the stream - this spawns a background task
// Use intelligence-enhanced system prompt if available
let prompt_arg = if enhanced_prompt.is_empty() { None } else { Some(enhanced_prompt) };
kernel.send_message_stream_with_prompt(&id, message, prompt_arg)
kernel.send_message_stream_with_prompt(&id, message.clone(), prompt_arg)
.await
.map_err(|e| format!("Failed to start streaming: {}", e))?
};
@@ -492,7 +492,7 @@ pub async fn agent_chat_stream(
// POST-CONVERSATION: record interaction + trigger reflection
crate::intelligence_hooks::post_conversation_hook(
&agent_id_str, &hb_state, &rf_state,
&agent_id_str, &message, &hb_state, &rf_state,
).await;
StreamChatEvent::Complete {
@@ -632,6 +632,7 @@ impl From<SkillContext> for zclaw_skills::SkillContext {
timeout_secs: 300,
network_allowed: true,
file_access_allowed: true,
llm: None, // Injected by Kernel.execute_skill()
}
}
}
@@ -800,7 +801,8 @@ pub async fn hand_list(
/// Execute a hand
///
/// Executes a hand with the given ID and input.
/// Returns the hand result as JSON.
/// If the hand has `needs_approval = true`, creates a pending approval instead.
/// Returns the hand result as JSON, or a pending status with approval ID.
#[tauri::command]
pub async fn hand_execute(
state: State<'_, KernelState>,
@@ -812,7 +814,26 @@ pub async fn hand_execute(
let kernel = kernel_lock.as_ref()
.ok_or_else(|| "Kernel not initialized. Call kernel_init first.".to_string())?;
// Execute hand
// Check if hand requires approval before execution
let hands = kernel.list_hands().await;
if let Some(hand_config) = hands.iter().find(|h| h.id == id) {
if hand_config.needs_approval {
let approval = kernel.create_approval(id.clone(), input).await;
return Ok(HandResult {
success: false,
output: serde_json::json!({
"status": "pending_approval",
"approval_id": approval.id,
"hand_id": approval.hand_id,
"message": "This hand requires approval before execution"
}),
error: None,
duration_ms: None,
});
}
}
// Execute hand directly
let result = kernel.execute_hand(&id, input).await
.map_err(|e| format!("Failed to execute hand: {}", e))?;
@@ -1139,6 +1160,63 @@ pub async fn hand_cancel(
Ok(serde_json::json!({ "status": "cancelled" }))
}
// ============================================================
// Hand Stub Commands (not yet fully implemented)
// ============================================================
/// Get detailed info for a single hand
#[tauri::command]
pub async fn hand_get(
state: State<'_, KernelState>,
name: String,
) -> Result<serde_json::Value, String> {
let kernel_lock = state.lock().await;
let kernel = kernel_lock.as_ref()
.ok_or_else(|| "Kernel not initialized".to_string())?;
let hands = kernel.list_hands().await;
let found = hands.iter().find(|h| h.id == name)
.ok_or_else(|| format!("Hand '{}' not found", name))?;
Ok(serde_json::to_value(found)
.map_err(|e| format!("Serialization error: {}", e))?)
}
/// Get status of a specific hand run
#[tauri::command]
pub async fn hand_run_status(
_state: State<'_, KernelState>,
hand_name: String,
run_id: String,
) -> Result<serde_json::Value, String> {
// Hand run tracking not yet implemented — return not-found status
Ok(serde_json::json!({
"status": "not_found",
"hand_name": hand_name,
"run_id": run_id,
"message": "Hand run history tracking is not yet implemented"
}))
}
/// List run history for a hand
#[tauri::command]
pub async fn hand_run_list(
_state: State<'_, KernelState>,
hand_name: String,
limit: Option<u32>,
offset: Option<u32>,
) -> Result<serde_json::Value, String> {
// Hand run history not yet implemented — return empty list
Ok(serde_json::json!({
"runs": [],
"hand_name": hand_name,
"total": 0,
"limit": limit.unwrap_or(20),
"offset": offset.unwrap_or(0),
"message": "Hand run history tracking is not yet implemented"
}))
}
// ============================================================
// Scheduled Task Commands
// ============================================================

View File

@@ -1341,6 +1341,9 @@ pub fn run() {
kernel_commands::hand_execute,
kernel_commands::hand_approve,
kernel_commands::hand_cancel,
kernel_commands::hand_get,
kernel_commands::hand_run_status,
kernel_commands::hand_run_list,
// Scheduled task commands
kernel_commands::scheduled_task_create,
kernel_commands::scheduled_task_list,

View File

@@ -362,6 +362,65 @@ export class KernelClient {
return invoke('agent_delete', { agentId });
}
// === Clone/Agent Adaptation (GatewayClient interface compatibility) ===
/**
* List clones — maps to listAgents() with field adaptation
*/
async listClones(): Promise<{ clones: any[] }> {
const agents = await this.listAgents();
const clones = agents.map((agent) => ({
id: agent.id,
name: agent.name,
role: agent.description,
model: agent.model,
createdAt: new Date().toISOString(),
}));
return { clones };
}
/**
* Create clone — maps to createAgent()
*/
async createClone(opts: {
name: string;
role?: string;
model?: string;
personality?: string;
communicationStyle?: string;
[key: string]: unknown;
}): Promise<{ clone: any }> {
const response = await this.createAgent({
name: opts.name,
description: opts.role,
model: opts.model,
});
const clone = {
id: response.id,
name: response.name,
role: opts.role,
model: opts.model,
personality: opts.personality,
communicationStyle: opts.communicationStyle,
createdAt: new Date().toISOString(),
};
return { clone };
}
/**
* Delete clone — maps to deleteAgent()
*/
async deleteClone(id: string): Promise<void> {
return this.deleteAgent(id);
}
/**
* Update clone — not supported in KernelClient mode
*/
async updateClone(_id: string, _updates: Record<string, unknown>): Promise<{ clone: unknown }> {
throw new Error('Agent update is not supported in local kernel mode');
}
// === Chat ===
/**