Implement skill self-evolution and skill_manage flow (#1874)

* chore: ignore .worktrees directory

* Add skill_manage self-evolution flow

* Fix CI regressions for skill_manage

* Address PR review feedback for skill evolution

* fix(skill-evolution): preserve history on delete

* fix(skill-evolution): tighten scanner fallbacks

* docs: add skill_manage e2e evidence screenshot

* fix(skill-manage): avoid blocking fs ops in session runtime

---------

Co-authored-by: Willem Jiang <willem.jiang@gmail.com>

backend/packages/harness/deerflow/config/__init__.py

@@ -2,6 +2,7 @@ from .app_config import get_app_config
 from .extensions_config import ExtensionsConfig, get_extensions_config
 from .memory_config import MemoryConfig, get_memory_config
 from .paths import Paths, get_paths
+from .skill_evolution_config import SkillEvolutionConfig
 from .skills_config import SkillsConfig
 from .tracing_config import (
     get_enabled_tracing_providers,
@@ -13,6 +14,7 @@ from .tracing_config import (
 
 __all__ = [
     "get_app_config",
+    "SkillEvolutionConfig",
     "Paths",
     "get_paths",
     "SkillsConfig",

backend/packages/harness/deerflow/config/app_config.py

@@ -15,6 +15,7 @@ from deerflow.config.guardrails_config import GuardrailsConfig, load_guardrails_
 from deerflow.config.memory_config import MemoryConfig, load_memory_config_from_dict
 from deerflow.config.model_config import ModelConfig
 from deerflow.config.sandbox_config import SandboxConfig
+from deerflow.config.skill_evolution_config import SkillEvolutionConfig
 from deerflow.config.skills_config import SkillsConfig
 from deerflow.config.stream_bridge_config import StreamBridgeConfig, load_stream_bridge_config_from_dict
 from deerflow.config.subagents_config import SubagentsAppConfig, load_subagents_config_from_dict
@@ -46,6 +47,7 @@ class AppConfig(BaseModel):
     tools: list[ToolConfig] = Field(default_factory=list, description="Available tools")
     tool_groups: list[ToolGroupConfig] = Field(default_factory=list, description="Available tool groups")
     skills: SkillsConfig = Field(default_factory=SkillsConfig, description="Skills configuration")
+    skill_evolution: SkillEvolutionConfig = Field(default_factory=SkillEvolutionConfig, description="Agent-managed skill evolution configuration")
     extensions: ExtensionsConfig = Field(default_factory=ExtensionsConfig, description="Extensions configuration (MCP servers and skills state)")
     tool_search: ToolSearchConfig = Field(default_factory=ToolSearchConfig, description="Tool search / deferred loading configuration")
     title: TitleConfig = Field(default_factory=TitleConfig, description="Automatic title generation configuration")

backend/packages/harness/deerflow/config/skill_evolution_config.py

@@ -0,0 +1,14 @@
+from pydantic import BaseModel, Field
+
+
+class SkillEvolutionConfig(BaseModel):
+    """Configuration for agent-managed skill evolution."""
+
+    enabled: bool = Field(
+        default=False,
+        description="Whether the agent can create and modify skills under skills/custom.",
+    )
+    moderation_model_name: str | None = Field(
+        default=None,
+        description="Optional model name for skill security moderation. Defaults to the primary chat model.",
+    )