上下文窗口膨胀的杀手 Agent Skill

from strands import Agent, AgentSkills, Skill

# 单个 skill 目录，不需要使用列表
plugin = AgentSkills(skills="./skills/pdf-processing")

# 父目录，会加载所有包含 SKILL.md 的子目录
plugin = AgentSkills(skills="./skills/")

# 混合来源
plugin = AgentSkills(skills=[
    "./skills/pdf-processing",     # 单个 skill 目录
    "./skills/",                   # 父目录（加载所有子 skill）
    Skill(                         # 在代码中定义 skill
        name="custom-greeting",
        description="Generate custom greetings",
        instructions="Always greet the user by name with enthusiasm.",
    ),
])

agent = Agent(plugins=[plugin])

from strands import Agent, AgentSkills
from strands_tools import file_read, shell

plugin = AgentSkills(skills="./skills/")

agent = Agent(
    plugins=[plugin],
    tools=[file_read, shell],
)

from strands import Skill

# 直接创建
skill = Skill(
    name="code-review",
    description="Review code for best practices and bugs",
    instructions="Review the provided code. Check for...",
)

# 从 SKILL.md 内容解析
skill = Skill.from_content("""---
name: code-review
description: Review code for best practices and bugs
---
Review the provided code. Check for...
""")

# 从指定目录加载
skill = Skill.from_file("./skills/code-review")

# 从父目录加载所有 skills
skills = Skill.from_directory("./skills/")

from strands import Agent, AgentSkills, Skill

plugin = AgentSkills(skills="./skills/pdf-processing")
agent = Agent(plugins=[plugin])

# 查看可用 skills
for skill in plugin.get_available_skills():
    print(f"{skill.name}: {skill.description}")

# 在运行时添加一个新 skill
new_skill = Skill(
    name="summarize",
    description="Summarize long documents",
    instructions="Read the document and produce a concise summary...",
)
plugin.set_available_skills(
    plugin.get_available_skills() + [new_skill]
)

# 替换所有 skills
plugin.set_available_skills(["./skills/new-set/"])

# 检查 agent 已激活了哪些 skills
activated = plugin.get_activated_skills(agent)
print(f"Activated skills: {activated}")

# main.py
import os
from dotenv import load_dotenv
from strands import Agent, AgentSkills
from strands.models.openai import OpenAIModel

load_dotenv()

model = OpenAIModel(
    client_args={"api_key": os.getenv("OPENAI_API_KEY")},
    model_id="gpt-5-mini",
)


plugin = AgentSkills(skills="./skills/")

agent = Agent(model=model, plugins=[plugin])

agent("hello")

# explain-code.py
import os
from dotenv import load_dotenv
from strands import Agent, AgentSkills
from strands.models.openai import OpenAIModel
from strands_tools import file_read, shell

load_dotenv()

model = OpenAIModel(
    client_args={"api_key": os.getenv("OPENAI_API_KEY")},
    model_id="gpt-5-mini",
)


plugin = AgentSkills(skills="./skills/")

agent = Agent(model=model, plugins=[plugin], tools=[file_read, shell])

agent("解释一下这个代码: explain-code.py")

# extract.py
import sys
import json
from pathlib import Path

import pymupdf


def extract_text(pdf_path: str) -> dict:
    """提取 PDF 文本内容"""
    try:
        pdf_file = Path(pdf_path)
        if not pdf_file.exists():
            return {"success": False, "error": f"File not found: {pdf_path}"}

        text_content = []
        pdf_document = pymupdf.open(pdf_path)

        for page_num in range(len(pdf_document)):
            page = pdf_document[page_num]
            page_text = page.get_text("text")
            if page_text.strip():
                text_content.append({"page": page_num + 1, "text": page_text})

        pdf_document.close()

        return {
            "success": True,
            "total_pages": len(text_content),
            "content": text_content,
        }
    except Exception as e:
        return {"success": False, "error": str(e)}


if __name__ == "__main__":
    pdf_path = sys.argv[1]
    result = extract_text(pdf_path)
    print(json.dumps(result, ensure_ascii=False, indent=2))