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https://github.com/shareAI-lab/analysis_claude_code.git
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feat: build an AI agent from 0 to 1 -- 11 progressive sessions
- 11 sessions from basic agent loop to autonomous teams - Python MVP implementations for each session - Mental-model-first docs in en/zh/ja - Interactive web platform with step-through visualizations - Incremental architecture: each session adds one mechanism
This commit is contained in:
CrazyBoyM
279
skills/agent-builder/scripts/init_agent.py
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279
skills/agent-builder/scripts/init_agent.py
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#!/usr/bin/env python3
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"""
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Agent Scaffold Script - Create a new agent project with best practices.
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Usage:
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python init_agent.py <agent-name> [--level 0-4] [--path <output-dir>]
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Examples:
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python init_agent.py my-agent # Level 1 (4 tools)
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python init_agent.py my-agent --level 0 # Minimal (bash only)
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python init_agent.py my-agent --level 2 # With TodoWrite
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python init_agent.py my-agent --path ./bots # Custom output directory
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"""
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import argparse
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import sys
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from pathlib import Path
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# Agent templates for each level
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TEMPLATES = {
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0: '''#!/usr/bin/env python3
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"""
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Level 0 Agent - Bash is All You Need (~50 lines)
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Core insight: One tool (bash) can do everything.
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Subagents via self-recursion: python {name}.py "subtask"
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"""
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from anthropic import Anthropic
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from dotenv import load_dotenv
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import subprocess
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import os
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load_dotenv()
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client = Anthropic(
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api_key=os.getenv("ANTHROPIC_API_KEY"),
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base_url=os.getenv("ANTHROPIC_BASE_URL")
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)
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MODEL = os.getenv("MODEL_NAME", "claude-sonnet-4-20250514")
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SYSTEM = """You are a coding agent. Use bash for everything:
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- Read: cat, grep, find, ls
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- Write: echo 'content' > file
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- Subagent: python {name}.py "subtask"
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"""
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TOOL = [{{
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"name": "bash",
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"description": "Execute shell command",
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"input_schema": {{"type": "object", "properties": {{"command": {{"type": "string"}}}}, "required": ["command"]}}
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}}]
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def run(prompt, history=[]):
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history.append({{"role": "user", "content": prompt}})
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while True:
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r = client.messages.create(model=MODEL, system=SYSTEM, messages=history, tools=TOOL, max_tokens=8000)
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history.append({{"role": "assistant", "content": r.content}})
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if r.stop_reason != "tool_use":
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return "".join(b.text for b in r.content if hasattr(b, "text"))
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results = []
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for b in r.content:
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if b.type == "tool_use":
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print(f"> {{b.input['command']}}")
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try:
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out = subprocess.run(b.input["command"], shell=True, capture_output=True, text=True, timeout=60)
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output = (out.stdout + out.stderr).strip() or "(empty)"
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except Exception as e:
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output = f"Error: {{e}}"
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results.append({{"type": "tool_result", "tool_use_id": b.id, "content": output[:50000]}})
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history.append({{"role": "user", "content": results}})
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if __name__ == "__main__":
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h = []
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print("{name} - Level 0 Agent\\nType 'q' to quit.\\n")
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while (q := input(">> ").strip()) not in ("q", "quit", ""):
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print(run(q, h), "\\n")
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''',
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1: '''#!/usr/bin/env python3
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"""
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Level 1 Agent - Model as Agent (~200 lines)
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Core insight: 4 tools cover 90% of coding tasks.
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The model IS the agent. Code just runs the loop.
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"""
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from anthropic import Anthropic
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from dotenv import load_dotenv
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from pathlib import Path
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import subprocess
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import os
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load_dotenv()
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client = Anthropic(
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api_key=os.getenv("ANTHROPIC_API_KEY"),
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base_url=os.getenv("ANTHROPIC_BASE_URL")
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)
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MODEL = os.getenv("MODEL_NAME", "claude-sonnet-4-20250514")
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WORKDIR = Path.cwd()
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SYSTEM = f"""You are a coding agent at {{WORKDIR}}.
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Rules:
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- Prefer tools over prose. Act, don't just explain.
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- Never invent file paths. Use ls/find first if unsure.
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- Make minimal changes. Don't over-engineer.
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- After finishing, summarize what changed."""
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TOOLS = [
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{{"name": "bash", "description": "Run shell command",
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"input_schema": {{"type": "object", "properties": {{"command": {{"type": "string"}}}}, "required": ["command"]}}}},
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{{"name": "read_file", "description": "Read file contents",
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"input_schema": {{"type": "object", "properties": {{"path": {{"type": "string"}}}}, "required": ["path"]}}}},
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{{"name": "write_file", "description": "Write content to file",
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"input_schema": {{"type": "object", "properties": {{"path": {{"type": "string"}}, "content": {{"type": "string"}}}}, "required": ["path", "content"]}}}},
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{{"name": "edit_file", "description": "Replace exact text in file",
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"input_schema": {{"type": "object", "properties": {{"path": {{"type": "string"}}, "old_text": {{"type": "string"}}, "new_text": {{"type": "string"}}}}, "required": ["path", "old_text", "new_text"]}}}},
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]
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def safe_path(p: str) -> Path:
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"""Prevent path escape attacks."""
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path = (WORKDIR / p).resolve()
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if not path.is_relative_to(WORKDIR):
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raise ValueError(f"Path escapes workspace: {{p}}")
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return path
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def execute(name: str, args: dict) -> str:
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"""Execute a tool and return result."""
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if name == "bash":
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dangerous = ["rm -rf /", "sudo", "shutdown", "> /dev/"]
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if any(d in args["command"] for d in dangerous):
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return "Error: Dangerous command blocked"
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try:
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r = subprocess.run(args["command"], shell=True, cwd=WORKDIR, capture_output=True, text=True, timeout=60)
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return (r.stdout + r.stderr).strip()[:50000] or "(empty)"
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except subprocess.TimeoutExpired:
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return "Error: Timeout (60s)"
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except Exception as e:
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return f"Error: {{e}}"
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if name == "read_file":
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try:
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return safe_path(args["path"]).read_text()[:50000]
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except Exception as e:
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return f"Error: {{e}}"
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if name == "write_file":
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try:
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p = safe_path(args["path"])
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p.parent.mkdir(parents=True, exist_ok=True)
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p.write_text(args["content"])
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return f"Wrote {{len(args['content'])}} bytes to {{args['path']}}"
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except Exception as e:
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return f"Error: {{e}}"
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if name == "edit_file":
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try:
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p = safe_path(args["path"])
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content = p.read_text()
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if args["old_text"] not in content:
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return f"Error: Text not found in {{args['path']}}"
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p.write_text(content.replace(args["old_text"], args["new_text"], 1))
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return f"Edited {{args['path']}}"
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except Exception as e:
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return f"Error: {{e}}"
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return f"Unknown tool: {{name}}"
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def agent(prompt: str, history: list = None) -> str:
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"""Run the agent loop."""
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if history is None:
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history = []
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history.append({{"role": "user", "content": prompt}})
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while True:
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response = client.messages.create(
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model=MODEL, system=SYSTEM, messages=history, tools=TOOLS, max_tokens=8000
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)
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history.append({{"role": "assistant", "content": response.content}})
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if response.stop_reason != "tool_use":
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return "".join(b.text for b in response.content if hasattr(b, "text"))
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results = []
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for block in response.content:
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if block.type == "tool_use":
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print(f"> {{block.name}}: {{str(block.input)[:100]}}")
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output = execute(block.name, block.input)
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print(f" {{output[:100]}}...")
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results.append({{"type": "tool_result", "tool_use_id": block.id, "content": output}})
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history.append({{"role": "user", "content": results}})
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if __name__ == "__main__":
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print(f"{name} - Level 1 Agent at {{WORKDIR}}")
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print("Type 'q' to quit.\\n")
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h = []
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while True:
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try:
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query = input(">> ").strip()
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except (EOFError, KeyboardInterrupt):
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break
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if query in ("q", "quit", "exit", ""):
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break
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print(agent(query, h), "\\n")
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''',
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}
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ENV_TEMPLATE = '''# API Configuration
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ANTHROPIC_API_KEY=sk-xxx
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ANTHROPIC_BASE_URL=https://api.anthropic.com
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MODEL_NAME=claude-sonnet-4-20250514
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'''
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def create_agent(name: str, level: int, output_dir: Path):
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"""Create a new agent project."""
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# Validate level
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if level not in TEMPLATES and level not in (2, 3, 4):
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print(f"Error: Level {level} not yet implemented in scaffold.")
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print("Available levels: 0 (minimal), 1 (4 tools)")
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print("For levels 2-4, copy from mini-claude-code repository.")
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sys.exit(1)
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# Create output directory
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agent_dir = output_dir / name
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agent_dir.mkdir(parents=True, exist_ok=True)
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# Write agent file
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agent_file = agent_dir / f"{name}.py"
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template = TEMPLATES.get(level, TEMPLATES[1])
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agent_file.write_text(template.format(name=name))
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print(f"Created: {agent_file}")
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# Write .env.example
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env_file = agent_dir / ".env.example"
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env_file.write_text(ENV_TEMPLATE)
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print(f"Created: {env_file}")
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# Write .gitignore
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gitignore = agent_dir / ".gitignore"
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gitignore.write_text(".env\n__pycache__/\n*.pyc\n")
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print(f"Created: {gitignore}")
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print(f"\nAgent '{name}' created at {agent_dir}")
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print(f"\nNext steps:")
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print(f" 1. cd {agent_dir}")
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print(f" 2. cp .env.example .env")
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print(f" 3. Edit .env with your API key")
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print(f" 4. pip install anthropic python-dotenv")
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print(f" 5. python {name}.py")
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def main():
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parser = argparse.ArgumentParser(
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description="Scaffold a new AI coding agent project",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""
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Levels:
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0 Minimal (~50 lines) - Single bash tool, self-recursion for subagents
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1 Basic (~200 lines) - 4 core tools: bash, read, write, edit
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2 Todo (~300 lines) - + TodoWrite for structured planning
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3 Subagent (~450) - + Task tool for context isolation
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4 Skills (~550) - + Skill tool for domain expertise
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"""
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)
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parser.add_argument("name", help="Name of the agent to create")
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parser.add_argument("--level", type=int, default=1, choices=[0, 1, 2, 3, 4],
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help="Complexity level (default: 1)")
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parser.add_argument("--path", type=Path, default=Path.cwd(),
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help="Output directory (default: current directory)")
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args = parser.parse_args()
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create_agent(args.name, args.level, args.path)
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if __name__ == "__main__":
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main()
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