steven_li
5ba5c7e4c1
集成新的Beaver后端服务到应用实例中，替换原有的nanobot实现。 主要变更包括： - 在Dockerfile和环境配置中添加Beaver相关路径和配置变量 - 更新工作目录结构从.nanobot到.beaver - 实现Beaver引擎加载器，支持配置文件加载和工具组装 - 添加内置工具如ListDirectoryTool、ReadFileTool、SearchFilesTool - 更新消息处理流程，支持通道适配器和网关模式 - 重构技能系统，支持显式工具提示和嵌入式检索 - 改进错误处理和生命周期管理 此变更使应用实例能够使用统一的Beaver后端进行AI代理运行时管理。
329 lines
12 KiB
Python
329 lines
12 KiB
Python
"""Beaver skills catalog loader。
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第一版目标非常明确：
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1. 扫描技能目录
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2. 读取 `SKILL.md`
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3. 解析前置元数据
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4. 生成可注入上下文的正文与索引
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这层不负责：
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1. 动态选择本轮应该启用哪些 skill
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2. skill review / publishing
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3. skill 自动学习
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这些决策属于 resolver 或更高层工作流。
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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import json
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from pathlib import Path
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from typing import Any
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from .utils import (
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check_requirements,
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escape_xml,
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get_missing_requirements,
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parse_frontmatter,
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parse_skill_metadata_blob,
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strip_frontmatter,
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)
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@dataclass(slots=True)
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class SkillRecord:
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"""单个 skill 的目录级元数据。"""
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name: str
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path: Path
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source: str
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class SkillsLoader:
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"""从 workspace/builtin 目录中发现并读取 skills。"""
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def __init__(
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self,
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workspace: str | Path,
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*,
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builtin_skills_dir: str | Path | None = None,
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extra_dirs: list[str | Path] | None = None,
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) -> None:
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self.workspace = Path(workspace)
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self.workspace_skills = self.workspace / "skills"
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self.builtin_skills = Path(builtin_skills_dir) if builtin_skills_dir is not None else Path(__file__).resolve().parent.parent / "builtin"
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self.extra_dirs = [Path(item) for item in (extra_dirs or [])]
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def list_skills(self, *, filter_unavailable: bool = True) -> list[SkillRecord]:
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"""列出当前可见的 skills。
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优先级：
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1. workspace
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2. extra/plugin 目录
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3. builtin
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重名 skill 只保留优先级更高的那一个。
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"""
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ordered_roots: list[tuple[str, Path]] = [
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("workspace", self.workspace_skills),
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*[("plugin", path) for path in self.extra_dirs],
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("builtin", self.builtin_skills),
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]
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found: dict[str, SkillRecord] = {}
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for source, root in ordered_roots:
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if not root.exists():
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continue
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for skill_dir in root.iterdir():
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skill_file = skill_dir / "SKILL.md"
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if not skill_dir.is_dir() or not skill_file.exists():
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continue
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name = skill_dir.name
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if name in found:
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continue
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record = SkillRecord(name=name, path=skill_file, source=source)
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if filter_unavailable and not self._record_available(record):
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continue
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found[name] = record
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return list(found.values())
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def load_skill(self, name: str) -> str | None:
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"""按名称加载 skill 原始内容。"""
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record = self._find_record(name)
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if record is None:
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return None
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return record.path.read_text(encoding="utf-8")
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def get_skill_record(self, name: str) -> SkillRecord | None:
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"""按名称返回 skill record。"""
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return self._find_record(name)
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def get_skill_metadata(self, name: str) -> dict[str, Any] | None:
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"""读取 skill frontmatter 元数据。"""
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content = self.load_skill(name)
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if content is None:
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return None
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metadata, _ = parse_frontmatter(content)
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return metadata
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def get_skill_tool_hints(self, name: str) -> list[str]:
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"""读取 skill 显式声明的推荐工具。
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第一版只信任显式 metadata，不从正文里猜：
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- `tools: read_file, search_files`
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- `tools: ["read_file", "search_files"]`
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- YAML-like list:
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tools:
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- read_file
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- search_files
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- 兼容 metadata JSON blob 里的 `tools`
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"""
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frontmatter = self.get_skill_metadata(name) or {}
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meta_blob = parse_skill_metadata_blob(frontmatter.get("metadata", ""))
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names = [
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*self._coerce_tool_names(frontmatter.get("tools")),
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*self._coerce_tool_names(meta_blob.get("tools")),
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*self._coerce_tool_names(meta_blob.get("required_tools")),
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]
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result: list[str] = []
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for item in names:
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if item and item not in result:
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result.append(item)
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return result
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def load_skills_for_context(self, skill_names: list[str]) -> str:
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"""加载指定 skills 的正文，并整理成上下文块。"""
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sections: list[str] = []
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for name in skill_names:
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content = self.load_skill(name)
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if not content:
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continue
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body = strip_frontmatter(content).strip()
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if not body:
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continue
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sections.append(f"## {name}\n\n{body}")
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return "\n\n".join(sections)
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def build_skills_summary(self) -> str:
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"""构建可注入 system prompt 的 skills index。
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虽然函数名还沿用 `summary`，但当前语义已经更接近 Hermes 的 skills index：
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- 这里只告诉模型“系统里有哪些 skill 可用”
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- 不负责把 skill 正文塞进 system prompt
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- 真正激活的 skill 正文由 resolver/builder 走显式消息注入
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"""
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skills = self.list_skills(filter_unavailable=False)
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if not skills:
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return ""
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lines = ["<skills>"]
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for record in skills:
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frontmatter = self.get_skill_metadata(record.name) or {}
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meta_blob = parse_skill_metadata_blob(frontmatter.get("metadata", ""))
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available = check_requirements(meta_blob)
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description = frontmatter.get("description") or record.name
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load_hint = f'Use skill_view(name="{record.name}") to load the full skill.'
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lines.append(f' <skill available="{str(available).lower()}">')
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lines.append(f" <name>{escape_xml(record.name)}</name>")
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lines.append(f" <description>{escape_xml(description)}</description>")
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lines.append(f" <load_hint>{escape_xml(load_hint)}</load_hint>")
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support_files = self.list_skill_supporting_files(record.name)
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if support_files:
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lines.append(" <supporting_files>")
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for file_path in support_files[:12]:
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lines.append(f" <file>{escape_xml(file_path)}</file>")
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if len(support_files) > 12:
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lines.append(" <file>...additional files omitted...</file>")
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lines.append(" </supporting_files>")
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if not available:
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missing = get_missing_requirements(meta_blob)
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if missing:
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lines.append(f" <requires>{escape_xml(missing)}</requires>")
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lines.append(" </skill>")
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lines.append("</skills>")
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return "\n".join(lines)
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def build_selection_candidates(self) -> list[dict[str, str]]:
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"""构建给 LLM selector 使用的候选 skill 摘要。
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这里刻意保持精简，只给：
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- `name`
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- `description`
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选择器的任务只是“从候选里挑名字”，不是直接阅读完整 skill 正文。
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真正激活后的 skill 正文仍然在后续阶段按需加载。
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"""
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candidates: list[dict[str, str]] = []
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for record in self.list_skills(filter_unavailable=True):
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frontmatter = self.get_skill_metadata(record.name) or {}
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description = str(frontmatter.get("description") or "").strip()
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if not description:
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raw_content = self.load_skill(record.name) or ""
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body = strip_frontmatter(raw_content).strip()
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if body:
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description = " ".join(body.splitlines()[:3])[:240].strip()
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candidates.append(
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{
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"name": record.name,
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"description": description or record.name,
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}
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)
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return candidates
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def list_skill_supporting_files(self, name: str) -> list[str]:
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"""列出 skill 目录下可按需查看的支持文件相对路径。"""
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record = self._find_record(name)
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if record is None:
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return []
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skill_dir = record.path.parent
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results: list[str] = []
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for subdir in ("references", "templates", "scripts", "assets"):
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root = skill_dir / subdir
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if not root.exists():
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continue
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for file in sorted(root.rglob("*")):
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if file.is_file() and not file.is_symlink():
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results.append(str(file.relative_to(skill_dir)))
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return results
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def view_skill(self, name: str, file_path: str | None = None) -> tuple[str, str] | None:
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"""读取 skill 正文或其支持文件。
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返回 `(display_name, content)`：
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- `display_name` 用于提示当前读取的是 skill 本体还是某个支持文件
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- `content` 为实际文本内容
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"""
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record = self._find_record(name)
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if record is None:
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return None
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if not self._record_available(record):
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frontmatter = self.get_skill_metadata(name) or {}
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meta_blob = parse_skill_metadata_blob(frontmatter.get("metadata", ""))
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missing = get_missing_requirements(meta_blob)
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detail = f" Missing requirements: {missing}." if missing else ""
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raise ValueError(f"Skill '{name}' is currently unavailable.{detail}")
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skill_dir = record.path.parent
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if not file_path:
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return ("SKILL.md", self._read_text_file(record.path, display_name="SKILL.md"))
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candidate = (skill_dir / file_path).resolve()
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try:
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candidate.relative_to(skill_dir.resolve())
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except ValueError as exc:
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raise ValueError("Requested skill file must stay within the skill directory") from exc
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if not candidate.exists() or not candidate.is_file():
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raise FileNotFoundError(f"Skill file '{file_path}' does not exist")
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display_name = str(candidate.relative_to(skill_dir))
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return (display_name, self._read_text_file(candidate, display_name=display_name))
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def get_always_skills(self) -> list[str]:
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"""返回标记为 always 的可用 skill 名称。"""
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result: list[str] = []
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for record in self.list_skills(filter_unavailable=True):
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frontmatter = self.get_skill_metadata(record.name) or {}
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meta_blob = parse_skill_metadata_blob(frontmatter.get("metadata", ""))
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if meta_blob.get("always") or str(frontmatter.get("always", "")).lower() == "true":
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result.append(record.name)
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return result
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@staticmethod
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def _coerce_tool_names(value: Any) -> list[str]:
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if value is None:
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return []
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if isinstance(value, str):
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raw = value.strip()
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if not raw:
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return []
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if raw.startswith("["):
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try:
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parsed = json.loads(raw)
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except Exception:
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parsed = None
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if isinstance(parsed, list):
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return [str(item).strip() for item in parsed if str(item).strip()]
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return [item.strip() for item in raw.split(",") if item.strip()]
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if isinstance(value, (list, tuple, set)):
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return [str(item).strip() for item in value if str(item).strip()]
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return []
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def _find_record(self, name: str) -> SkillRecord | None:
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for record in self.list_skills(filter_unavailable=False):
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if record.name == name:
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return record
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return None
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def _record_available(self, record: SkillRecord) -> bool:
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content = record.path.read_text(encoding="utf-8")
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frontmatter, _ = parse_frontmatter(content)
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meta_blob = parse_skill_metadata_blob(frontmatter.get("metadata", ""))
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return check_requirements(meta_blob)
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@staticmethod
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def _read_text_file(path: Path, *, display_name: str) -> str:
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try:
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return path.read_text(encoding="utf-8")
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except UnicodeDecodeError as exc:
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raise ValueError(
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f"Skill file '{display_name}' is not UTF-8 text and cannot be viewed with skill_view."
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) from exc
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def _skill_available(self, name: str) -> bool:
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record = self._find_record(name)
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if record is None:
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return False
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return self._record_available(record)
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