feat(beaver): 完成Task Team功能v1实现，重构后端架构支持统一内核
新增内部Task系统，包括验证、反馈门控机制，实现自动质量验证 (通过率>=0.75)和用户反馈闭环(satisfied/revise/abandon)。 实现Agent Team v1协调器，支持sequence/parallel/dag执行策略， sub-agent复用主AgentLoop，每个run使用独立memory snapshot。 建立Skill学习pipeline，包含draft/审核/发布/回滚完整生命周期， 通过Task验证通过且用户满意才生成学习候选。 重构目录结构，移除third_party依赖，建立统一engine内核， 所有agent共享运行时基础组件。 更新ContextBuilder清理provider消息字段，增强SkillContext版本管理， 集成TaskExecutionPlanner和TaskSkillResolver实现技能解析机制。
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app-instance/backend/beaver/skills/learning/missing_skill.py
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app-instance/backend/beaver/skills/learning/missing_skill.py
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"""Synthesize draft-only skills for missing sub-agent guidance."""
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from __future__ import annotations
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import json
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import re
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from dataclasses import dataclass
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from typing import TYPE_CHECKING, Any
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from beaver.engine.context import SkillContext
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from beaver.engine.providers import ProviderBundle
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from beaver.skills.drafts import DraftService
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from beaver.skills.specs import SkillDraft
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from beaver.skills.specs.serialization import canonical_hash
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if TYPE_CHECKING:
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from beaver.tasks.models import TaskRecord
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@dataclass(slots=True)
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class MissingSkillDraftResult:
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draft: SkillDraft
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skill_context: SkillContext
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class MissingSkillSynthesizer:
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"""Create a draft skill and an ephemeral SkillContext for the current run."""
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async def synthesize(
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self,
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*,
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task: TaskRecord,
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user_message: str,
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attempt_index: int,
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node_id: str,
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node_task: str,
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skill_query: str,
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required_capabilities: list[str],
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provider_bundle: ProviderBundle,
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draft_service: DraftService,
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) -> MissingSkillDraftResult:
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provider = provider_bundle.auxiliary_provider or provider_bundle.main_provider
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runtime = provider_bundle.auxiliary_runtime or provider_bundle.main_runtime
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model = getattr(runtime, "model", None)
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payload = self._fallback_payload(skill_query=skill_query, node_task=node_task, capabilities=required_capabilities)
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try:
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response = await provider.chat(
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messages=[
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{
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"role": "system",
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"content": (
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"You create concise Beaver skill drafts. Return only JSON with keys: "
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"skill_name, description, content, tags."
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),
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},
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{
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"role": "user",
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"content": (
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"Create a procedural skill draft for this missing Task sub-agent guidance.\n\n"
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f"Task goal:\n{task.goal}\n\n"
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f"Current user request:\n{user_message}\n\n"
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f"Node id: {node_id}\n"
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f"Node task:\n{node_task}\n\n"
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f"Skill query:\n{skill_query}\n"
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f"Required capabilities: {required_capabilities}\n\n"
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"The content must be actionable guidance for a temporary sub-agent. "
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"Do not include implementation claims or publish metadata."
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),
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},
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],
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tools=None,
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model=model,
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max_tokens=1200,
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temperature=0,
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)
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payload = self._parse_payload(response.content or "") or payload
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except Exception:
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payload = payload
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skill_name = _slug(str(payload.get("skill_name") or skill_query or node_id))
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content = str(payload.get("content") or "").strip()
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if not content:
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content = str(self._fallback_payload(skill_query=skill_query, node_task=node_task, capabilities=required_capabilities)["content"])
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frontmatter = {
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"description": str(payload.get("description") or f"Draft guidance for {skill_query or node_id}").strip(),
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"tags": [str(item) for item in payload.get("tags") or ["generated", "task-sub-agent"]],
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"metadata": {
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"origin": "missing_task_subagent_skill",
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"task_id": task.task_id,
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"node_id": node_id,
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"attempt_index": attempt_index,
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"skill_query": skill_query,
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"required_capabilities": list(required_capabilities),
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},
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}
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draft = draft_service.create_new_skill_draft(
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skill_name=skill_name,
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proposed_content=content,
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proposed_frontmatter=frontmatter,
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created_by="task-skill-resolver",
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reason="generated_for_missing_task_subagent_skill",
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trigger_session_id=task.session_id,
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evidence_refs=[
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{
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"task_id": task.task_id,
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"session_id": task.session_id,
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"attempt_index": attempt_index,
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"node_id": node_id,
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"skill_query": skill_query,
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"required_capabilities": list(required_capabilities),
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}
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],
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)
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context = SkillContext(
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name=f"draft:{draft.skill_name}",
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content=draft.proposed_content,
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version=f"draft:{draft.draft_id}",
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content_hash=canonical_hash(draft.proposed_content),
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activation_reason="generated_missing_skill",
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tool_hints=[],
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)
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return MissingSkillDraftResult(draft=draft, skill_context=context)
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@staticmethod
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def _parse_payload(text: str) -> dict[str, Any] | None:
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cleaned = text.strip()
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if cleaned.startswith("```"):
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lines = cleaned.splitlines()
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if len(lines) >= 3 and lines[0].startswith("```") and lines[-1].startswith("```"):
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cleaned = "\n".join(lines[1:-1]).strip()
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if cleaned.lower().startswith("json"):
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cleaned = cleaned[4:].strip()
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start = cleaned.find("{")
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end = cleaned.rfind("}")
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if start >= 0 and end >= start:
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cleaned = cleaned[start : end + 1]
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try:
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payload = json.loads(cleaned)
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except json.JSONDecodeError:
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return None
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return payload if isinstance(payload, dict) else None
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@staticmethod
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def _fallback_payload(*, skill_query: str, node_task: str, capabilities: list[str]) -> dict[str, Any]:
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title = skill_query or node_task or "task subagent guidance"
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capability_lines = "\n".join(f"- {item}" for item in capabilities) or "- Follow the node task precisely."
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return {
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"skill_name": _slug(title),
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"description": f"Draft guidance for {title}.",
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"tags": ["generated", "task-sub-agent"],
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"content": (
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f"# {title}\n\n"
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"Use this draft guidance only for the current delegated sub-task.\n\n"
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"## Objective\n"
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f"{node_task or title}\n\n"
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"## Capabilities to apply\n"
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f"{capability_lines}\n\n"
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"## Output\n"
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"Return concise evidence, decisions, and unresolved risks for the main Agent to synthesize."
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),
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}
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def _slug(value: str) -> str:
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cleaned = re.sub(r"[^a-zA-Z0-9]+", "-", value.strip().lower()).strip("-")
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return cleaned[:64].strip("-") or "generated-task-subagent-skill"
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