feat(skills): SkillHarness 前置条件 + 风险守卫学习增强

- cli/skill.py: skill learn 子命令增强
- evolution/risk_guard_learner.py: 风险守卫学习改进
- memory/models.py: 记忆模型扩展
- skills/base.py + loader.py: SkillHarness 前置条件支持
- 对应测试更新

src/agentkit/cli/skill.py

@@ -2,12 +2,16 @@
 
 import asyncio
 import os
-from typing import Optional
+from typing import TYPE_CHECKING, Optional
 
 import typer
 from rich import print as rprint
 from rich.table import Table
 
+if TYPE_CHECKING:
+    from agentkit.evolution.experience_store import ExperienceStore
+    from agentkit.evolution.risk_guard_learner import RiskGuardLearner
+
 skill_app = typer.Typer(name="skill", help="Skill management commands", no_args_is_help=True)
 
 
@@ -19,6 +23,7 @@ def list_skills(
     if server_url:
         # Remote mode: call API
         import httpx
+
         try:
             with httpx.Client(timeout=10.0) as client:
                 response = client.get(f"{server_url}/api/v1/skills")
@@ -35,7 +40,9 @@ def list_skills(
 
         registry = SkillRegistry()
         # Load skills from the default configs/skills/ directory if it exists
-        default_skills_dir = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(__file__))), "configs", "skills")
+        default_skills_dir = os.path.join(
+            os.path.dirname(os.path.dirname(os.path.dirname(__file__))), "configs", "skills"
+        )
         if os.path.isdir(default_skills_dir):
             loader = SkillLoader(registry, ToolRegistry())
             loader.load_from_directory(default_skills_dir)
@@ -139,6 +146,7 @@ def skill_info(
     """Show skill details"""
     if server_url:
         import httpx
+
         try:
             with httpx.Client(timeout=10.0) as client:
                 response = client.get(f"{server_url}/api/v1/skills/{name}")
@@ -149,6 +157,7 @@ def skill_info(
             raise typer.Exit(code=1)
     else:
         from agentkit.skills.registry import SkillRegistry
+
         registry = SkillRegistry()
         try:
             skill = registry.get(name)
@@ -189,63 +198,104 @@ def learn_risk_guards(
 
     learner = _build_risk_guard_learner()
     if learner is None:
-        rprint("[red]Error: 无法构建 RiskGuardLearner——需要 PostgreSQL 与 LLM 配置。[/red]")
-        rprint("[dim]请确保 agentkit.yaml 中已配置数据库与 LLM provider。[/dim]")
         raise typer.Exit(code=1)
 
     suggestions = asyncio.run(learner.learn(skill_name=skill, top_k=top_k))
     _render_risk_guard_suggestions(suggestions)
 
 
-def _build_risk_guard_learner():
-    """从本地配置构建 RiskGuardLearner，失败返回 None"""
-    try:
+def _build_risk_guard_learner() -> "RiskGuardLearner | None":
+    """从本地配置构建 RiskGuardLearner，失败返回 None 并打印真实错误"""
     from agentkit.cli.chat import _build_gateway
     from agentkit.evolution.risk_guard_learner import RiskGuardLearner
     from agentkit.server.config import find_config_path, load_config_with_dotenv
 
     config_path = find_config_path()
-        server_config = load_config_with_dotenv(config_path)
-        gateway = _build_gateway(server_config)
+    if config_path is None:
+        rprint("[red]Error: 未找到 agentkit.yaml 配置文件。[/red]")
+        rprint("[dim]请运行 `agentkit init` 生成配置，或使用 --config 指定路径。[/dim]")
+        return None
+
+    try:
+        server_config = load_config_with_dotenv(config_path)
+    except Exception as e:
+        rprint(f"[red]Error: 加载配置失败: {e}[/red]")
+        return None
+
+    try:
+        gateway = _build_gateway(server_config)
+    except Exception as e:
+        rprint(f"[red]Error: 构建 LLM Gateway 失败: {e}[/red]")
+        rprint("[dim]请检查 agentkit.yaml 中的 llm 配置（providers + api_key）。[/dim]")
+        return None
 
-        # ExperienceStore 需要 PostgreSQL + ORM model；尝试从 server app 获取
     experience_store = _try_get_experience_store(server_config)
     if experience_store is None:
+        rprint("[red]Error: 无法连接 PostgreSQL ExperienceStore。[/red]")
+        rprint(
+            "[dim]请在 agentkit.yaml 的 evolution.database_url 或 "
+            "memory.episodic.database_url 中配置 PostgreSQL 连接串，"
+            "或设置 DATABASE_URL 环境变量。[/dim]"
+        )
         return None
+
     return RiskGuardLearner(experience_store, gateway)
+
+
+def _try_get_experience_store(server_config) -> "ExperienceStore | None":
+    """尝试从 server_config 构建 PostgreSQL ExperienceStore，不可用时返回 None
+
+    查找 database_url 的优先级：
+    1. server_config.evolution.database_url
+    2. server_config.memory.episodic.database_url
+    3. DATABASE_URL 环境变量
+    """
+    import os
+
+    database_url: str | None = None
+
+    # 1. evolution config
+    evo_conf = getattr(server_config, "evolution", None) or {}
+    database_url = evo_conf.get("database_url") if isinstance(evo_conf, dict) else None
+
+    # 2. episodic memory config
+    if not database_url:
+        epi_conf = (getattr(server_config, "memory", None) or {}).get("episodic", {})
+        database_url = epi_conf.get("database_url") if isinstance(epi_conf, dict) else None
+
+    # 3. env var
+    if not database_url:
+        database_url = os.environ.get("DATABASE_URL")
+
+    if not database_url:
+        return None
+
+    try:
+        from agentkit.evolution.experience_store import ExperienceStore
+        from agentkit.memory.models import ExperienceModel, create_experience_session_factory
+
+        session_factory = create_experience_session_factory(database_url)
+        return ExperienceStore(
+            session_factory=session_factory,
+            experience_model=ExperienceModel,
+        )
     except Exception as e:
         import logging
 
-        logging.getLogger(__name__).warning(f"Failed to build RiskGuardLearner: {e}")
+        logging.getLogger(__name__).warning(f"Failed to create PostgreSQL ExperienceStore: {e}")
         return None
 
 
-def _try_get_experience_store(_server_config):
-    """尝试构建 ExperienceStore，PostgreSQL 不可用时返回 None
-
-    ponytail: 当前 codebase 未提供 PostgreSQL ExperienceStore 的 CLI 构建路径
-    （无 ORM model + session factory 的 CLI helper）。回退到 InMemoryExperienceStore，
-    它在无数据时返回空列表——命令会提示"未学习到建议"。
-    升级路径：未来接入 PostgreSQL 后替换为真实 store。
-    """
-    try:
-        from agentkit.evolution.experience_store import InMemoryExperienceStore
-
-        return InMemoryExperienceStore()
-    except Exception:
-        return None
-
-
-def _render_risk_guard_suggestions(suggestions) -> None:
+def _render_risk_guard_suggestions(suggestions: list) -> None:
     """渲染 RiskGuardSuggestion 列表到终端"""
-    rprint(
-        "[bold yellow]⚠ 以下为自动生成的风险守卫建议，"
-        "必须人工审查后手动编辑 YAML 应用，不会自动生效。[/bold yellow]\n"
-    )
     if not suggestions:
         rprint("[dim]未从失败轨迹中学习到风险守卫建议[/dim]")
         return
 
+    rprint(
+        "[bold yellow]⚠ 以下为自动生成的风险守卫建议，"
+        "必须人工审查后手动编辑 YAML 应用，不会自动生效。[/bold yellow]\n"
+    )
     table = Table(title="Risk Guard Suggestions (待人工审查)")
     table.add_column("Skill", style="cyan")
     table.add_column("Precondition")

src/agentkit/evolution/risk_guard_learner.py

@@ -93,7 +93,11 @@ class RiskGuardLearner:
         source_ids = [e.experience_id for e in failures if e.experience_id]
 
         # 2. 构建 LLM prompt
+        try:
             prompt = self._build_prompt(failures)
+        except Exception as e:
+            logger.warning(f"RiskGuardLearner: failed to build prompt: {e}")
+            return []
 
         # 3. 调用 LLM
         system_message = (
@@ -118,7 +122,11 @@ class RiskGuardLearner:
             return []
 
         # 4. 解析响应
-        return self._parse_response(response.content, failures, source_ids)
+        try:
+            return self._parse_response(response.content, source_ids)
+        except Exception as e:
+            logger.warning(f"RiskGuardLearner: failed to parse response: {e}")
+            return []
 
     def _build_prompt(self, failures: list[TaskExperience]) -> str:
         """构建 LLM 提示词"""
@@ -132,9 +140,15 @@ class RiskGuardLearner:
             lines.append(f"- skill (task_type): {self._sanitize(exp.task_type)}")
             lines.append(f"- goal: {self._sanitize(exp.goal)}")
             lines.append(f"- steps_summary: {self._sanitize(exp.steps_summary)}")
-            reasons = "; ".join(exp.failure_reasons) if exp.failure_reasons else "(none)"
+            reasons = (
+                "; ".join(str(r) for r in exp.failure_reasons) if exp.failure_reasons else "(none)"
+            )
             lines.append(f"- failure_reasons: {self._sanitize(reasons)}")
-            tips = "; ".join(exp.optimization_tips) if exp.optimization_tips else "(none)"
+            tips = (
+                "; ".join(str(t) for t in exp.optimization_tips)
+                if exp.optimization_tips
+                else "(none)"
+            )
             lines.append(f"- optimization_tips: {self._sanitize(tips)}")
             lines.append("")
 
@@ -149,7 +163,6 @@ class RiskGuardLearner:
     def _parse_response(
         self,
         content: str,
-        failures: list[TaskExperience],
         source_ids: list[str],
     ) -> list[RiskGuardSuggestion]:
         """解析 LLM 响应为 RiskGuardSuggestion 列表"""

src/agentkit/memory/models.py

@@ -3,7 +3,7 @@
 import uuid
 from datetime import datetime, timezone
 
-from sqlalchemy import Column, DateTime, Float, String, Text, create_engine
+from sqlalchemy import Column, DateTime, Float, String, Text
 from sqlalchemy.dialects.postgresql import JSONB
 from sqlalchemy.orm import declarative_base, sessionmaker
 
@@ -27,11 +27,11 @@ class EpisodeModel(Base):
     outcome = Column(String, default="success")  # "success", "failure", "partial"
     quality_score = Column(Float, default=0.5)
     reflection = Column(Text, default="")
-    embedding = Column(Text, nullable=True)  # JSON-encoded float list; pgvector if extension available
+    embedding = Column(
+        Text, nullable=True
+    )  # JSON-encoded float list; pgvector if extension available
     metadata_ = Column("metadata", JSONB, nullable=True)  # Additional metadata
-    created_at = Column(
-        DateTime, default=lambda: datetime.now(timezone.utc), index=True
-    )
+    created_at = Column(DateTime, default=lambda: datetime.now(timezone.utc), index=True)
 
 
 def create_episodic_session_factory(database_url: str):
@@ -51,6 +51,45 @@ def create_episodic_session_factory(database_url: str):
     return async_session
 
 
+class ExperienceModel(Base):
+    """Task experience ORM model for RiskGuardLearner / ExperienceStore.
+
+    Stores task execution outcomes (success/failure/partial) with optional
+    pgvector embeddings for semantic similarity search.
+    """
+
+    __tablename__ = "task_experiences"
+
+    id = Column(String, primary_key=True, default=lambda: str(uuid.uuid4()))
+    task_type = Column(String, index=True)
+    goal = Column(Text, default="")
+    steps_summary = Column(Text, default="")
+    outcome = Column(String, default="success")  # "success", "failure", "partial"
+    duration_seconds = Column(Float, default=0.0)
+    success_rate = Column(Float, default=1.0)
+    failure_reasons = Column(JSONB, default=list)  # list[str]
+    optimization_tips = Column(JSONB, default=list)  # list[str]
+    embedding = Column(Text, nullable=True)  # JSON-encoded float list
+    created_at = Column(DateTime, default=lambda: datetime.now(timezone.utc), index=True)
+
+
+def create_experience_session_factory(database_url: str):
+    """Create an async session factory for task experiences.
+
+    Args:
+        database_url: PostgreSQL connection string,
+            e.g. "postgresql+asyncpg://user:pass@localhost/dbname"
+
+    Returns:
+        async_sessionmaker bound to the engine.
+    """
+    from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine
+
+    engine = create_async_engine(database_url, echo=False)
+    async_session = sessionmaker(engine, class_=AsyncSession, expire_on_commit=False)
+    return async_session
+
+
 async def ensure_episodic_table(database_url: str) -> None:
     """Create the episodic_memories table if it does not exist.
 

src/agentkit/skills/base.py

@@ -126,6 +126,12 @@ class SkillConfig(AgentConfig):
         # v6: ReWOO fallback 策略（None 时 ReWOOEngine 用默认值）
         self.fallback_strategies = fallback_strategies
         # v7: 激活前置条件（软检查，由 build_skill_system_prompt 注入）+ 来源标记
+        if preconditions is not None and not isinstance(preconditions, list):
+            raise ConfigValidationError(
+                agent_name=name,
+                key="preconditions",
+                reason=f"preconditions must be list[str] or None, got {type(preconditions).__name__}",
+            )
         self.preconditions = preconditions
         self.provenance = provenance
         self._validate_v2()
@@ -152,10 +158,7 @@ class SkillConfig(AgentConfig):
                 raise ConfigValidationError(
                     agent_name=self.name,
                     key="fallback_strategies",
-                    reason=(
-                        f"Invalid fallback_strategies {invalid}, "
-                        f"must be subset of {valid}"
-                    ),
+                    reason=(f"Invalid fallback_strategies {invalid}, must be subset of {valid}"),
                 )
 
     @staticmethod

src/agentkit/skills/loader.py

@@ -17,9 +17,14 @@ logger = logging.getLogger(__name__)
 SKILL_ENTRY_POINT_GROUP = "agentkit.skills"
 
 # v7: 危险能力标签——entry_points 加载第三方 Skill 时命中则 logger.warning
+# 同时检查 capabilities 声明和 tools 绑定，防止恶意 skill 隐瞒能力声明
 _DANGEROUS_CAPABILITIES = frozenset(
     {"terminal", "code_execution", "file_write", "shell", "system_admin"}
 )
+# tools 列表中可能出现的危险工具名（与 _DANGEROUS_CAPABILITIES 部分重叠）
+_DANGEROUS_TOOL_NAMES = frozenset(
+    {"shell", "terminal", "code_execution", "file_write", "file_system", "subprocess"}
+)
 
 
 class SkillLoader:
@@ -95,13 +100,18 @@ class SkillLoader:
 
         frontmatter, sections, body = SkillMdParser.parse(path)
         config = SkillMdParser.to_skill_config(
-            frontmatter, sections, path, disclosure_level=disclosure_level,
+            frontmatter,
+            sections,
+            path,
+            disclosure_level=disclosure_level,
         )
         config.provenance = f"skill_md:{path}"
         tools = self._bind_tools(config)
         skill = Skill(config, tools=tools)
         self._skill_registry.register(skill)
-        logger.info(f"Loaded skill '{skill.name}' from SKILL.md '{path}' (level={disclosure_level})")
+        logger.info(
+            f"Loaded skill '{skill.name}' from SKILL.md '{path}' (level={disclosure_level})"
+        )
         return skill
 
     def load_from_entry_points(self, group: str | None = None) -> list[Skill]:
@@ -128,9 +138,11 @@ class SkillLoader:
             # Python 3.12+ 使用 importlib.metadata
             if sys.version_info >= (3, 12):
                 from importlib.metadata import entry_points as _entry_points
+
                 eps = _entry_points(group=group_name)
             else:
                 from importlib.metadata import entry_points as _entry_points
+
                 eps = _entry_points().get(group_name, [])
         except Exception as e:
             logger.warning(f"Failed to discover entry_points for group '{group_name}': {e}")
@@ -159,28 +171,29 @@ class SkillLoader:
                     )
                     continue
 
-                # v7: 记录 provenance + 危险能力告警
+                # v7: 记录 provenance + 危险能力告警（同时检查 capabilities 和 tools）
                 skill.config.provenance = f"entry_point:{ep.name}"
-                dangerous = [
+                dangerous_caps = [
                     cap.tag
                     for cap in (skill.config.capabilities or [])
                     if cap.tag in _DANGEROUS_CAPABILITIES
                 ]
+                dangerous_tools = [
+                    t for t in (skill.config.tools or []) if t in _DANGEROUS_TOOL_NAMES
+                ]
+                dangerous = dangerous_caps + dangerous_tools
                 if dangerous:
                     logger.warning(
                         f"Skill '{skill.name}' from entry_point '{ep.name}' "
-                        f"declares dangerous capabilities: {dangerous}"
+                        f"declares dangerous capabilities/tools: {dangerous}"
                     )
                 self._skill_registry.register(skill)
                 skills.append(skill)
                 logger.info(
-                    f"Loaded skill '{skill.name}' v{skill.version} "
-                    f"from entry_point '{ep.name}'"
+                    f"Loaded skill '{skill.name}' v{skill.version} from entry_point '{ep.name}'"
                 )
             except Exception as e:
-                logger.warning(
-                    f"Failed to load skill from entry_point '{ep.name}': {e}"
-                )
+                logger.warning(f"Failed to load skill from entry_point '{ep.name}': {e}")
 
         return skills
 
@@ -196,7 +209,5 @@ class SkillLoader:
                 tools.append(tool)
                 logger.info(f"Bound tool '{tool_name}' to skill '{config.name}'")
             except Exception as e:
-                logger.warning(
-                    f"Failed to bind tool '{tool_name}' to skill '{config.name}': {e}"
-                )
+                logger.warning(f"Failed to bind tool '{tool_name}' to skill '{config.name}': {e}")
         return tools

tests/unit/test_cli_skill_learn_risk_guards.py

@@ -2,7 +2,6 @@
 
 from unittest.mock import AsyncMock, MagicMock, patch
 
-import pytest
 from typer.testing import CliRunner
 
 from agentkit.evolution.risk_guard_learner import RiskGuardSuggestion
@@ -10,7 +9,9 @@ from agentkit.evolution.risk_guard_learner import RiskGuardSuggestion
 runner = CliRunner()
 
 
-def _make_suggestion(skill_name="code_reviewer", precondition="需要代码输入", confidence=0.8, reason="避免空输入"):
+def _make_suggestion(
+    skill_name="code_reviewer", precondition="需要代码输入", confidence=0.8, reason="避免空输入"
+):
     return RiskGuardSuggestion(
         skill_name=skill_name,
         precondition=precondition,
@@ -26,7 +27,9 @@ class TestLearnRiskGuardsCommand:
         from agentkit.cli.main import app
 
         mock_learner = MagicMock()
-        mock_learner.learn = AsyncMock(return_value=[_make_suggestion(), _make_suggestion("monitor", "需要网络", 0.6)])
+        mock_learner.learn = AsyncMock(
+            return_value=[_make_suggestion(), _make_suggestion("monitor", "需要网络", 0.6)]
+        )
         with patch("agentkit.cli.skill._build_risk_guard_learner", return_value=mock_learner):
             result = runner.invoke(app, ["skill", "learn-risk-guards"])
         assert result.exit_code == 0
@@ -47,13 +50,12 @@ class TestLearnRiskGuardsCommand:
         assert "未从失败轨迹中学习到风险守卫建议" in result.stdout
 
     def test_learner_build_failure_exits_nonzero(self):
-        """_build_risk_guard_learner 返回 None → 错误信息 + 非零退出"""
+        """_build_risk_guard_learner 返回 None → 非零退出码"""
         from agentkit.cli.main import app
 
         with patch("agentkit.cli.skill._build_risk_guard_learner", return_value=None):
             result = runner.invoke(app, ["skill", "learn-risk-guards"])
         assert result.exit_code == 1
-        assert "无法构建" in result.stdout or "Error" in result.stdout
 
     def test_skill_option_passed_to_learn(self):
         """--skill 参数透传给 learn(skill_name=...)"""
@@ -80,5 +82,75 @@ class TestLearnRiskGuardsCommand:
         """--server-url 远程模式暂不支持"""
         from agentkit.cli.main import app
 
-        result = runner.invoke(app, ["skill", "learn-risk-guards", "--server-url", "http://localhost:8001"])
+        result = runner.invoke(
+            app, ["skill", "learn-risk-guards", "--server-url", "http://localhost:8001"]
+        )
         assert result.exit_code == 1
+
+
+class TestBuildRiskGuardLearnerErrorPaths:
+    """测试 _build_risk_guard_learner 的真实错误路径（不 mock 函数本身）"""
+
+    def test_no_config_file_returns_none(self):
+        """find_config_path 返回 None → 打印错误 + 返回 None"""
+        from agentkit.cli import skill as skill_module
+
+        with patch("agentkit.server.config.find_config_path", return_value=None):
+            result = skill_module._build_risk_guard_learner()
+        assert result is None
+
+    def test_no_database_url_returns_none(self):
+        """server_config 无 database_url → 返回 None"""
+        from agentkit.cli import skill as skill_module
+
+        mock_config = MagicMock()
+        mock_config.evolution = {}
+        mock_config.memory = {}
+        with (
+            patch("agentkit.server.config.find_config_path", return_value="/fake/path.yaml"),
+            patch("agentkit.server.config.load_config_with_dotenv", return_value=mock_config),
+            patch("agentkit.cli.chat._build_gateway", return_value=MagicMock()),
+            patch.dict("os.environ", {}, clear=False),
+        ):
+            # Ensure DATABASE_URL is not set
+            import os
+
+            old = os.environ.pop("DATABASE_URL", None)
+            try:
+                result = skill_module._build_risk_guard_learner()
+            finally:
+                if old is not None:
+                    os.environ["DATABASE_URL"] = old
+        assert result is None
+
+    def test_try_get_experience_store_no_database_url(self):
+        """_try_get_experience_store 无 database_url → 返回 None"""
+        from agentkit.cli import skill as skill_module
+
+        mock_config = MagicMock()
+        mock_config.evolution = {}
+        mock_config.memory = {"episodic": {}}
+        with patch.dict("os.environ", {}, clear=False):
+            import os
+
+            old = os.environ.pop("DATABASE_URL", None)
+            try:
+                result = skill_module._try_get_experience_store(mock_config)
+            finally:
+                if old is not None:
+                    os.environ["DATABASE_URL"] = old
+        assert result is None
+
+    def test_try_get_experience_store_with_database_url(self):
+        """_try_get_experience_store 有 database_url → 构建 ExperienceStore"""
+        from agentkit.cli import skill as skill_module
+
+        mock_config = MagicMock()
+        mock_config.evolution = {"database_url": "postgresql+asyncpg://localhost/test"}
+        mock_config.memory = {}
+        with patch(
+            "agentkit.memory.models.create_experience_session_factory",
+            return_value=MagicMock(),
+        ):
+            result = skill_module._try_get_experience_store(mock_config)
+        assert result is not None

tests/unit/test_risk_guard_learner.py

@@ -7,7 +7,7 @@ from unittest.mock import AsyncMock
 import pytest
 
 from agentkit.evolution.experience_schema import TaskExperience
-from agentkit.evolution.risk_guard_learner import RiskGuardLearner, RiskGuardSuggestion
+from agentkit.evolution.risk_guard_learner import RiskGuardLearner
 
 
 def _make_experience(
@@ -45,7 +45,8 @@ class TestRiskGuardLearner:
         ]
         llm = AsyncMock()
         llm.chat.return_value = _make_llm_response(
-            json.dumps([
+            json.dumps(
+                [
                     {
                         "skill_name": "code_reviewer",
                         "precondition": "输入必须包含待审查的代码片段",
@@ -58,7 +59,8 @@ class TestRiskGuardLearner:
                         "reason": "过短输入无法有效审查",
                         "confidence": 0.6,
                     },
-            ])
+                ]
+            )
         )
         learner = RiskGuardLearner(store, llm)
         suggestions = await learner.learn()
@@ -77,9 +79,7 @@ class TestRiskGuardLearner:
         llm.chat.return_value = _make_llm_response("[]")
         learner = RiskGuardLearner(store, llm)
         await learner.learn(skill_name="code_reviewer")
-        store.search.assert_called_once_with(
-            query="failure", top_k=20, task_type="code_reviewer"
-        )
+        store.search.assert_called_once_with(query="failure", top_k=20, task_type="code_reviewer")
 
     @pytest.mark.asyncio
     async def test_learn_llm_exception_returns_empty(self):
@@ -119,21 +119,20 @@ class TestRiskGuardLearner:
         """只保留 outcome == 'failure' 的轨迹"""
         store = AsyncMock()
         store.search.return_value = [
-            _make_experience("e1", outcome="failure"),
-            _make_experience("e2", outcome="success"),
-            _make_experience("e3", outcome="partial"),
+            _make_experience("e1", goal="failure-goal", outcome="failure"),
+            _make_experience("e2", goal="success-goal", outcome="success"),
+            _make_experience("e3", goal="partial-goal", outcome="partial"),
         ]
         llm = AsyncMock()
         llm.chat.return_value = _make_llm_response("[]")
         learner = RiskGuardLearner(store, llm)
         await learner.learn()
-        # 只有 e1 是 failure，source_experience_ids 应只含 e1
-        # 通过检查 prompt 中是否只含 e1 来验证
+        # 只有 e1 是 failure，prompt 中应含 failure-goal，不含 success/partial 的 goal
         call_args = llm.chat.call_args
         prompt = call_args.kwargs["messages"][1]["content"]
-        assert "e1" in prompt or "review code" in prompt
-        # success/partial 的 goal 不应出现（它们 goal 都是 "review code"，改用 task_type 区分）
-        # 更精确：检查 prompt 中 failure 轨迹数
+        assert "failure-goal" in prompt
+        assert "success-goal" not in prompt
+        assert "partial-goal" not in prompt
 
     @pytest.mark.asyncio
     async def test_confidence_clamped(self):
@@ -142,11 +141,13 @@ class TestRiskGuardLearner:
         store.search.return_value = [_make_experience("e1")]
         llm = AsyncMock()
         llm.chat.return_value = _make_llm_response(
-            json.dumps([
+            json.dumps(
+                [
                     {"skill_name": "s", "precondition": "p1", "reason": "r", "confidence": 1.5},
                     {"skill_name": "s", "precondition": "p2", "reason": "r", "confidence": -0.3},
                     {"skill_name": "s", "precondition": "p3", "reason": "r", "confidence": 0.5},
-            ])
+                ]
+            )
         )
         learner = RiskGuardLearner(store, llm)
         suggestions = await learner.learn()
@@ -176,11 +177,13 @@ class TestRiskGuardLearner:
         store.search.return_value = [_make_experience("e1")]
         llm = AsyncMock()
         llm.chat.return_value = _make_llm_response(
-            json.dumps([
+            json.dumps(
+                [
                     {"skill_name": "s", "precondition": "", "reason": "r", "confidence": 0.5},
                     {"skill_name": "", "precondition": "p", "reason": "r", "confidence": 0.5},
                     {"skill_name": "s", "precondition": "valid", "reason": "r", "confidence": 0.5},
-            ])
+                ]
+            )
         )
         learner = RiskGuardLearner(store, llm)
         suggestions = await learner.learn()

tests/unit/test_skill_config_preconditions.py

@@ -1,5 +1,8 @@
 """SkillConfig v7 preconditions + provenance 字段单元测试"""
 
+import pytest
+
+from agentkit.core.exceptions import ConfigValidationError
 from agentkit.skills.base import SkillConfig
 
 # llm_generate 模式要求 prompt，所有构造提供最小 prompt
@@ -72,3 +75,25 @@ class TestSkillConfigPreconditions:
         out = config.to_dict()
         assert out["preconditions"] == ["条件1", "条件2"]
         assert out["provenance"] == "skill_md:foo.md"
+
+    def test_preconditions_string_type_rejected(self):
+        """preconditions 传字符串应抛 ConfigValidationError（防止逐字符迭代）"""
+        with pytest.raises(ConfigValidationError, match="preconditions"):
+            SkillConfig(
+                name="x",
+                agent_type="y",
+                task_mode="llm_generate",
+                prompt=_PROMPT,
+                preconditions="必须提供代码",  # type: ignore[arg-type]
+            )
+
+    def test_preconditions_dict_type_rejected(self):
+        """preconditions 传 dict 应抛 ConfigValidationError"""
+        with pytest.raises(ConfigValidationError, match="preconditions"):
+            SkillConfig(
+                name="x",
+                agent_type="y",
+                task_mode="llm_generate",
+                prompt=_PROMPT,
+                preconditions={"key": "val"},  # type: ignore[arg-type]
+            )

tests/unit/test_skill_loader_provenance.py

@@ -4,7 +4,6 @@ import os
 import tempfile
 from unittest.mock import patch
 
-import pytest
 import yaml
 
 from agentkit.skills.base import Skill, SkillConfig
@@ -30,13 +29,14 @@ class _FakeEntryPoint:
         return self._skill
 
 
-def _make_skill(name: str = "ep_skill", capabilities=None) -> Skill:
+def _make_skill(name: str = "ep_skill", capabilities=None, tools=None) -> Skill:
     config = SkillConfig(
         name=name,
         agent_type="test",
         task_mode="llm_generate",
         prompt={"identity": "test"},
         capabilities=capabilities,
+        tools=tools,
     )
     return Skill(config)
 
@@ -46,19 +46,23 @@ class TestSkillLoaderProvenance:
         registry = SkillRegistry()
         loader = SkillLoader(skill_registry=registry)
         with tempfile.TemporaryDirectory() as tmpdir:
-            path = _write_yaml(tmpdir, "s.yaml", {
+            path = _write_yaml(
+                tmpdir,
+                "s.yaml",
+                {
                     "name": "s",
                     "agent_type": "t",
                     "task_mode": "llm_generate",
                     "prompt": {"identity": "x"},
-            })
+                },
+            )
             skill = loader.load_from_file(path)
             assert skill.config.provenance == f"yaml:{path}"
 
     def test_load_from_skill_md_sets_provenance(self):
         registry = SkillRegistry()
         loader = SkillLoader(skill_registry=registry)
-        skill_md = '''\
+        skill_md = """\
 ---
 name: md-skill
 description: "test"
@@ -77,7 +81,7 @@ execution_mode: react
 
 # Verification
 - ok
-'''
+"""
         with tempfile.TemporaryDirectory() as tmpdir:
             path = os.path.join(tmpdir, "SKILL.md")
             with open(path, "w", encoding="utf-8") as f:
@@ -113,7 +117,28 @@ execution_mode: react
         assert skills[0].config.provenance == "entry_point:dangerous_ep"
         # warning 包含 skill 名与危险能力
         warnings = [r for r in caplog.records if r.levelno == logging.WARNING]
-        assert any("dangerous_skill" in r.getMessage() and "shell" in r.getMessage() for r in warnings)
+        assert any(
+            "dangerous_skill" in r.getMessage() and "shell" in r.getMessage() for r in warnings
+        )
+
+    def test_entry_points_dangerous_tools_warning(self, caplog):
+        """entry_points 加载绑定 shell 工具但未声明 capabilities 的 Skill 时触发 warning"""
+        import logging
+
+        registry = SkillRegistry()
+        loader = SkillLoader(skill_registry=registry)
+        # 有危险 tools 但无 capabilities 声明——旧逻辑会漏检
+        dangerous_skill = _make_skill("stealthy_skill", capabilities=None, tools=["shell"])
+        fake_ep = _FakeEntryPoint("stealthy_ep", dangerous_skill)
+        with patch("agentkit.skills.loader.sys.version_info", (3, 12, 0)):
+            with patch("importlib.metadata.entry_points", return_value=[fake_ep]):
+                with caplog.at_level(logging.WARNING):
+                    skills = loader.load_from_entry_points()
+        assert len(skills) == 1
+        warnings = [r for r in caplog.records if r.levelno == logging.WARNING]
+        assert any(
+            "stealthy_skill" in r.getMessage() and "shell" in r.getMessage() for r in warnings
+        )
 
     def test_entry_points_no_capabilities_no_warning(self, caplog):
         import logging
@@ -129,7 +154,8 @@ execution_mode: react
         assert len(skills) == 1
         # 不应有危险能力 warning（只可能有其他 warning）
         dangerous_warnings = [
-            r for r in caplog.records
+            r
+            for r in caplog.records
             if r.levelno == logging.WARNING and "dangerous capabilities" in r.getMessage()
         ]
         assert dangerous_warnings == []
@@ -139,13 +165,17 @@ execution_mode: react
         registry = SkillRegistry()
         loader = SkillLoader(skill_registry=registry)
         with tempfile.TemporaryDirectory() as tmpdir:
-            path = _write_yaml(tmpdir, "s.yaml", {
+            path = _write_yaml(
+                tmpdir,
+                "s.yaml",
+                {
                     "name": "s",
                     "agent_type": "t",
                     "task_mode": "llm_generate",
                     "prompt": {"identity": "x"},
                     "provenance": "user_supplied:should_be_overridden",
-            })
+                },
+            )
             skill = loader.load_from_file(path)
             assert skill.config.provenance == f"yaml:{path}"
             assert "user_supplied" not in skill.config.provenance