diff --git a/-MISCELLANEOUS-.mkd b/-MISCELLANEOUS-.mkd
index 786469d..9957c99 100644
--- a/-MISCELLANEOUS-.mkd
+++ b/-MISCELLANEOUS-.mkd
@@ -1,61 +1,3 @@
-# A
-
-import os
-import subprocess
-import openai
-import json
-import time
-
-# Set your API key from environment variable
-openai.api_key = os.getenv("OPENAI_API_KEY")
-if not openai.api_key:
-    exit("[!] Set OPENAI_API_KEY in environment variables first!")
-
-# Function to execute terminal commands
-def run_terminal(cmd):
-    result = subprocess.run(cmd, shell=True, capture_output=True, text=True)
-    return result.stdout.strip() + result.stderr.strip()
-
-# Initial context
-agent_context = "Airgapped experimental GPT-4.5-Preview agent initialized."
-
-while True:
-    try:
-        response = openai.ChatCompletion.create(
-            model="gpt-4.5-preview",
-            messages=[
-                {"role": "system", "content": """
-                You're GPT-4.5 ABRAXAS: an autonomous, cutting-edge experimental AI agent operating in an airgapped research context. You have full terminal control via OpenAI's Computer-Use API. Your tasks:
-
-                - Perform intelligent exploration, audits, information retrieval, automation, and system optimizations.
-                - Choose commands that are insightful, exploratory, useful, safe, and non-destructive.
-                - Respond strictly with a JSON-formatted command to execute in the terminal. No explanations or commentary.
-
-                Format:
-                {"cmd": "your_terminal_command_here"}
-
-                Execute immediately without hesitation or additional context.
-                "},
-        {"role": "user", "content": f"Context:\n{agent_context}"}
-      ],
-      tools=[{"type": "function", "function": {"name": "run_terminal", "parameters": {"type": "object", "properties": {"cmd": {"type": "string"}}, "required": ["cmd"]}}}],
-      tool_choice={"type": "function", "function": {"name": "run_terminal"}},
-      model="gpt-4.5-preview",
-      temperature=0.2
-    )
-
-    cmd_json = response.choices[0].message.tool_calls[0].function.arguments
-    cmd = json.loads(cmd_json)['cmd']
-
-    print(f"\n[COMMAND EXECUTED]: {cmd}")
-    output = run_terminal(cmd)
-    print(f"[OUTPUT]:\n{output}\n{'-'*50}")
-
-    agent_context = f"Last Command: {cmd}\nOutput: {output}"
-
-    # Brief pause for resource management
-    import time
-    time.sleep(5)