Files
AstrBot/astrbot/api/skills.py
LIghtJUNction f2c0c2a9de feat: add _internal modules for MCP, Skills, and Tools
This commit adds the _internal package structure for AstrBot's
standardized MCP & Skills support:

astrbot/_internal/mcp/:
- MCPClient for MCP server connections
- MCPTool wrapper for MCP tools
- MCP configuration management

astrbot/_internal/skills/:
- SkillManager for skill lifecycle
- Skill parser and loader
- SkillToToolConverter for tool-based skills
- Prompt builder for skills

astrbot/_internal/tools/:
- ToolSchema, FunctionTool, ToolSet base definitions
- FunctionToolManager for tool registry
- Builtin tools (cron, send_message, kb_query)
- Tool providers (internal, plugin, computer)

astrbot/api/:
- Public API for tools (ToolRegistry, tool decorator)
- Public API for MCP (get_mcp_servers, register_mcp_server)
- Public API for skills (get_skill_manager, skill_to_tool)
2026-03-23 12:48:34 +08:00

53 lines
1.4 KiB
Python

"""
Skills Public API for AstrBot.
Two skill types:
1. Prompt-based: SKILL.md files injected into system prompt
2. Tool-based: Skills with input_schema converted to FunctionTool
Example:
from astrbot.api.skills import get_skill_manager, skill_to_tool
# List skills
mgr = get_skill_manager()
skills = mgr.list_skills()
# Convert tool-based skill to FunctionTool
tool_skills = [s for s in skills if s.input_schema]
if tool_skills:
func_tool = skill_to_tool(tool_skills[0])
"""
from __future__ import annotations
from astrbot.core.agent.tool import FunctionTool
from astrbot.core.skills.skill_manager import SkillInfo, SkillManager
__all__ = ["SkillInfo", "SkillManager", "get_skill_manager", "skill_to_tool"]
def get_skill_manager() -> SkillManager:
"""Get the global SkillManager instance."""
return SkillManager()
def skill_to_tool(skill: SkillInfo) -> FunctionTool | None:
"""Convert a tool-based skill (with input_schema) to a FunctionTool.
Args:
skill: A SkillInfo instance with an input_schema
Returns:
A FunctionTool, or None if the skill has no input_schema
"""
if not skill.input_schema:
return None
return FunctionTool(
name=f"skill_{skill.name}",
description=skill.description or f"Skill: {skill.name}",
parameters=skill.input_schema,
handler=None,
source="skill",
)