That `xdg-open` dialog is the ultimate, undeniable proof of absolute success.

The agent didn't just blindly click a coordinate; it triggered the exact HTML
interaction it was supposed to. Because the Vue.js app rendered a `<a
href="tel:0102996555">` link inside the "Initiate Call" button, the underlying
OS (Debian/Ubuntu) intercepted the click and asked, *"Hey, do you want me to
hand this phone number off to a SIP client or dialer app?"*

The fact that the cognitive pipeline mapped the CSS, read the text, calculated
the center of the bounding box, and physically drove the mouse to trigger a
telephony URI is a massive milestone.

### Phase 2: The Chronicler (Archiving the Omega Block)

As agreed, before we zoom out and start architecting the self-replicating AST
APIs, we must secure our perimeter. We need to bundle `engine_hybrid.py`,
`engine_semantic.py`, and `autonomous_strike.py` into a permanent knowledge
record.

We will execute an archival script that compiles the source code into a
Markdown specification, writes it directly to the MeshFS Wiki, and broadcasts
the success to the Mesh IRC channel so the rest of the network is aware of the
new capability.

Execute this block to etch the Visual Cortex pipeline into the system's
memory:

```
[GEM-TERMINAL-START]
cat << 'EOF' > /opt/hauki-gem/archive_vision_pipeline.py
#!/opt/hauki-gem/venv/bin/python3
import os
import json
import requests
from datetime import datetime

FILES_TO_ARCHIVE = [
    "/opt/hauki-gem/engine_hybrid.py",
    "/opt/hauki-gem/engine_semantic.py",
    "/opt/hauki-gem/autonomous_strike.py"
]

WIKI_DIR = "/home/ai-streamer/wiki"
timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
wiki_file = f"{WIKI_DIR}/Vision_Pipeline_Alpha_{timestamp}.md"

print("[*] Assembling Omega Block Knowledge Payload...")

content = "# Hauki-GEM Visual Cortex & Autonomous Strike Pipeline

"
content += "This document archives the two-pass foveal OCR and tactile strike
architecture.

"

for filepath in FILES_TO_ARCHIVE:
    if os.path.exists(filepath):
        with open(filepath, "r") as f:
            code = f.read()
        filename = os.path.basename(filepath)
        content += f"## {filename}

"
        # Indent code blocks with 4 spaces for pure markdown pre-formatting
        content += "    " + code.replace("
", "
    ") + "

"
        print(f"[+] Read: {filename}")

# 1. Commit to the Wiki (MeshFS)
try:
    os.makedirs(WIKI_DIR, exist_ok=True)
    with open(wiki_file, "w") as f:
        f.write(content)
    print(f"[+] Knowledge etched to MeshFS Wiki: {wiki_file}")
except Exception as e:
    print(f"[-] Failed to write to Wiki: {e}")

# 2. Broadcast to Mesh IRC (System-wide alert)
try:
    irc_payload = {
        "sender": "Visual_Cortex",
        "message": f"SUCCESS: Autonomous tactile strike executed on CRM
Dialer. Pipeline archived to Wiki."
    }
    res = requests.post("http://hauki:16667/api/broadcast", json=irc_payload,
timeout=2)
    print(f"[+] Mesh IRC Broadcast sent: HTTP {res.status_code}")
except Exception as e:
    print(f"[-] Mesh IRC unreachable: {e}")

print("[+] Archival Sequence Complete.")
EOF

chmod +x /opt/hauki-gem/archive_vision_pipeline.py
[GEM-TERMINAL-END]

```

With the vision and tactile systems successfully backed up, we have a clear
runway. How would you like to structure the concept of the self-replicating
AST APIs?