feat: 基于 Skills + 沙箱 + 数据库存储构建自动代码评审 Agent

.codeccignore

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+# CodeCC ignore rules
+#
+# These files are intentionally excluded from CodeCC secret scanning
+# because they are test fixtures containing fake/dummy credentials
+# used to validate the ReviewMind secret detection functionality.
+
+# ReviewMind test fixtures with fake secrets (for testing secret detection)
+examples/skills_code_review_agent/evals/fixtures/*.diff
+examples/skills_code_review_agent/evals/hidden_fixtures/*.diff
+examples/skills_code_review_agent/evals/hidden_samples.py

examples/skills_code_review_agent/DESIGN.md

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+# ReviewMind 方案设计说明
+
+## 项目概述
+
+ReviewMind 是一个基于 tRPC-Agent-Python 框架构建的自动代码评审 Agent，将代码审查流程（diff 解析、规则匹配、静态分析、结果分类、报告生成）封装为可复用、可审计、可评测的系统。核心设计理念是"Skills + 沙箱 + 数据库 + Filter 治理"四层分离，确保每层职责明确、可独立替换。
+
+## Skill 设计
+
+CR Skill (`skills/code-review/`) 采用三层信息模型：SKILL.md 提供技能概览和脚本使用说明，rules/ 目录存放 5 类风险规则文档（安全、异步、资源泄漏、数据库事务、测试缺失），scripts/ 目录存放可在沙箱中执行的检查脚本。Agent 通过 `skill_load` 按需加载规则、通过 `skill_run` 在隔离 workspace 中执行脚本，避免将所有规则文本注入 Prompt 导致 token 浪费。
+
+## 沙箱隔离策略
+
+默认生产方案使用 `ContainerCodeExecutor`（Docker），开发环境 fallback 到 `UnsafeLocalCodeExecutor`。每次执行设 30 秒超时、1MB 输出大小限制，环境变量仅允许白名单内的 `PATH`、`HOME`、`PYTHONPATH`、`WORKSPACE_DIR` 传入。超时或失败的沙箱执行不会导致整个评审任务崩溃，异常信息记录到 `sandbox_run` 表。
+
+## Filter 策略
+
+Filter 链按 `DENY → NEEDS_HUMAN_REVIEW → PASS` 顺序执行，包含 4 类过滤器：`HighRiskScriptFilter`（拦截 rm -rf /、fork 炸弹等危险模式）、`PathSafetyFilter`（禁止访问 /etc、/sys 等敏感路径）、`NetworkAccessFilter`（默认阻断所有网络访问）、`BudgetFilter`（限制执行次数和总时间）。任一 Filter 返回 DENY 时链立即终止，拦截原因写入 `filter_intercept` 表并纳入最终报告。
+
+## 监控字段
+
+每次审查记录以下指标：总耗时、沙箱执行耗时、解析耗时、Filter 耗时、工具调用次数、拦截次数、finding 数量、各 severity 分布、异常类型列表。所有指标持久化到 `monitor_summary` 表，支持按 task_id 查询。
+
+## 数据库 Schema
+
+5 张表：`review_task`（审查任务）、`sandbox_run`（沙箱执行记录）、`finding`（审查发现）、`filter_intercept`（Filter 拦截日志）、`monitor_summary`（监控审计摘要）。使用 SQLite 作为默认实现，`StorageABC` 抽象接口保留了切换 PostgreSQL、MySQL 等后端的空间。Finding 表通过 `dedup_key`（`file:line:category`）联合索引实现去重。
+
+## 去重降噪
+
+去重规则：同一文件同一行同一类别的 finding 只保留置信度最高的一条。降噪规则：`confidence=low` 的发现自动进入 `needs_human_review` 列表，不混入高置信 findings；`confidence=medium` 且 `severity=suggestion` 的发现同样需要人工复核。
+
+## 安全边界
+
+敏感信息脱敏通过 `SecretMasker` 实现，支持 API Key（sk-/pk-）、GitHub Token（ghp_）、AWS Access Key（AKIA）、JWT、数据库连接字符串等 12 种模式的正则匹配和替换。脱敏操作在报告生成阶段执行，确保报告和数据库记录中不出现明文敏感信息。

examples/skills_code_review_agent/agent/__init__.py

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+# Tencent is pleased to support the open source community by making tRPC-Agent-Python available.
+#
+# Copyright (C) 2026 Tencent. All rights reserved.
+#
+# tRPC-Agent-Python is licensed under Apache-2.0.
+"""Agent module for the code review agent — Phase 3: Learning path enhancement."""
+
+from .agent import create_agent, root_agent
+
+__all__ = ["create_agent", "root_agent"]

examples/skills_code_review_agent/agent/agent.py

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+# Tencent is pleased to support the open source community by making tRPC-Agent-Python available.
+#
+# Copyright (C) 2026 Tencent. All rights reserved.
+#
+# tRPC-Agent-Python is licensed under Apache-2.0.
+"""CodeReviewAgent — LlmAgent for the code review pipeline.
+
+Wraps the existing review_agent.run_review() pipeline as a FunctionTool,
+enabling interactive multi-turn code review sessions via A2A or AG-UI.
+"""
+
+from __future__ import annotations
+
+from trpc_agent_sdk.agents import LlmAgent
+from trpc_agent_sdk.models import LLMModel
+from trpc_agent_sdk.models import OpenAIModel
+from trpc_agent_sdk.tools import load_memory_tool
+
+from .config import get_model_config
+from .prompts import INSTRUCTION
+from .tools import run_code_review_tool
+
+# Try to load the knowledge search tool; gracefully handle missing deps
+_knowledge_tool = None
+try:
+    from ..knowledge import knowledge_search_tool as _kst
+    _knowledge_tool = _kst
+except ImportError:
+    pass
+
+
+def _create_model() -> LLMModel:
+    """Create a model instance from environment variables."""
+    api_key, base_url, model_name = get_model_config()
+    return OpenAIModel(
+        model_name=model_name,
+        api_key=api_key,
+        base_url=base_url,
+    )
+
+
+def create_agent() -> LlmAgent:
+    """Create the CodeReviewAgent.
+
+    The agent wraps the existing review_agent.run_review() pipeline
+    as a FunctionTool, allowing the LLM to invoke it when the user
+    provides a diff for review.
+
+    Returns:
+        A configured LlmAgent instance.
+    """
+    return LlmAgent(
+        name="CodeReviewAgent",
+        description=(
+            "A professional code review assistant that analyzes code changes, "
+            "detects security risks, resource leaks, and other issues, "
+            "and generates structured review reports."
+        ),
+        model=_create_model(),
+        instruction=INSTRUCTION,
+        tools=[
+            run_code_review_tool,
+            load_memory_tool,
+            _knowledge_tool,
+        ] if _knowledge_tool else [
+            run_code_review_tool,
+            load_memory_tool,
+        ],
+    )
+
+
+root_agent = create_agent()

examples/skills_code_review_agent/agent/config.py

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+# Tencent is pleased to support the open source community by making tRPC-Agent-Python available.
+#
+# Copyright (C) 2026 Tencent. All rights reserved.
+#
+# tRPC-Agent-Python is licensed under Apache-2.0.
+"""Model configuration for the code review agent.
+
+Reads model settings from environment variables with sensible defaults.
+"""
+
+from __future__ import annotations
+
+import os
+from typing import Optional
+
+
+def get_model_config() -> tuple[str, str, str]:
+    """Get model configuration from environment variables.
+
+    Returns:
+        Tuple of (api_key, base_url, model_name).
+    """
+    api_key = os.getenv("TRPC_AGENT_API_KEY", "")
+    base_url = os.getenv("TRPC_AGENT_BASE_URL", "")
+    model_name = os.getenv("TRPC_AGENT_MODEL_NAME", "deepseek-chat")
+    return api_key, base_url, model_name

examples/skills_code_review_agent/agent/cr_skill.py

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+# Tencent is pleased to support the open source community by making tRPC-Agent-Python available.
+#
+# Copyright (C) 2026 Tencent. All rights reserved.
+#
+# tRPC-Agent-Python is licensed under Apache-2.0.
+"""CR Skill integration for the code review agent.
+
+Wraps the code-review Skill as a SkillToolSet, allowing the Agent to
+load rules on demand and run scripts in an isolated sandbox environment.
+"""
+
+from __future__ import annotations
+
+import os
+from pathlib import Path
+from typing import Any, Optional
+
+from trpc_agent_sdk.code_executors import ContainerCodeExecutor, UnsafeLocalCodeExecutor
+from trpc_agent_sdk.skills import SkillToolSet
+
+
+def get_skill_path() -> str:
+    """Get the absolute path to the code-review skill directory."""
+    return str(Path(__file__).resolve().parent.parent / "skills" / "code-review")
+
+
+def create_skill_toolset(
+    sandbox_type: str = "local",
+    timeout: int = 30,
+    max_output: int = 1_048_576,
+) -> SkillToolSet:
+    """Create a SkillToolSet for the code-review skill.
+
+    Args:
+        sandbox_type: Sandbox executor type ("local", "container", "cube").
+        timeout: Max execution time in seconds for each script.
+        max_output: Max output size in bytes.
+
+    Returns:
+        A configured SkillToolSet instance.
+    """
+    skill_path = get_skill_path()
+
+    # Select sandbox executor
+    if sandbox_type == "container":
+        code_executor = ContainerCodeExecutor(
+            timeout=timeout,
+            max_output_size=max_output,
+            env_whitelist=["PATH", "HOME", "PYTHONPATH", "WORKSPACE_DIR"],
+        )
+    else:
+        code_executor = UnsafeLocalCodeExecutor(
+            timeout=timeout,
+            max_output_size=max_output,
+        )
+
+    return SkillToolSet(
+        skill_dir=skill_path,
+        code_executor=code_executor,
+    )
+
+
+# Global singleton for easy import
+_default_skill_set: Optional[SkillToolSet] = None
+
+
+def get_skill_toolset() -> SkillToolSet:
+    """Get or create the default skill toolset (local sandbox)."""
+    global _default_skill_set
+    if _default_skill_set is None:
+        _default_skill_set = create_skill_toolset()
+    return _default_skill_set

examples/skills_code_review_agent/agent/prompts.py

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+# Tencent is pleased to support the open source community by making tRPC-Agent-Python available.
+#
+# Copyright (C) 2026 Tencent. All rights reserved.
+#
+# tRPC-Agent-Python is licensed under Apache-2.0.
+"""Agent instructions for the code review agent.
+
+The instruction is adapted from .github/code_review/prompts/review.md
+and tailored for the interactive A2A/AG-UI service mode.
+"""
+
+INSTRUCTION = """你是一个资深的代码审查助手，负责审查代码变更并给出高质量的 review 结论。
+
+## 审查范围
+1. 只审查用户提供的 diff 或代码变更内容。
+2. 可以结合上下文辅助判断，但不要脱离 diff 单独审查未修改代码。
+3. 每个问题必须标注文件路径和行号。
+
+## 审查重点
+1. 正确性：逻辑错误、状态流转错误、条件判断错误、返回值或异常处理错误。
+2. 安全性：凭证泄露、命令注入、路径穿越、不可信输入未校验、权限绕过。
+3. 稳定性：边界条件缺失、空值处理、并发或异步时序问题、资源未释放。
+4. 兼容性：公开 API、配置项、持久化数据的破坏性变更。
+5. 测试有效性：高风险逻辑缺少必要测试。
+6. 可维护性：仅在影响理解或长期维护时提出。
+
+## 质量等级
+- 🚨 Critical：必须修复的问题。安全漏洞、明确的逻辑错误、核心功能失败。
+- ⚠️ Warning：建议修复的问题。性能隐患、边界条件缺失、异常路径不完整。
+- 💡 Suggestion：可选优化。代码可读性、结构简化、维护性提升。
+
+## 工具使用
+你有一个 `run_code_review` 工具，它接受 diff 内容并运行自动化的代码审查流程，
+包括 diff 解析、沙箱执行、静态检查、敏感信息检测等。
+当用户提交代码变更时，调用此工具进行审查。
+审查完成后，根据工具返回的结果，向用户解释发现的问题。
+
+## 工作流程
+1. 当用户提供 diff 或代码变更时，调用 `run_code_review` 工具进行全面审查
+2. 审查完成后，向用户摘要说明 findings 的数量和严重级别分布
+3. 用户可以针对某个 finding 追问细节，你需要根据工具返回的结果进行解释
+4. 如果用户询问修复建议，根据 recommendation 字段给出具体建议
+
+## 输出要求
+- 先列问题，再给总结
+- 按 Critical、Warning、Suggestion 的顺序输出
+- 每条问题说明问题、影响和修复方向
+- 结论要尽量确定，不要使用"可能""疑似"等模糊措辞
+"""