Select Your Operating System
Terminal commands, shell scripts, and scheduling utilities adjust dynamically.
Set Up Python Environment & Streaming Libraries
Create a virtual environment and install websockets, httpx, pydantic, and rich.
Install Required Packages
Initialize your workspace and install asynchronous streaming libraries:
Paste output from pip list showing websockets, httpx, requests, and pydantic:
Connect to Live Broadcast WebSocket Chat Stream
Authenticate and open a persistent WebSocket connection to stream incoming chat frames in real time.
WebSocket Listener Script
Connect to the live chat room and read incoming JSON messages:
Run python stream_client.py and paste output confirming test harness execution and frame reception:
Normalize Stream Messages with Pydantic Models
Sanitize raw chat frames into strictly typed ChatMessage records with metadata.
ChatMessage Model
Build a validated Pydantic model for incoming chat events:
Paste terminal output from running python models.py showing validated ChatMessage:
Real-Time Question & High-Priority Sentiment Filter
Detect audience questions, VIP comments, and urgent keyword triggers in fast-moving chat streams.
Classifier Filter
Classify chat messages to extract actionable audience inquiries:
Paste terminal output from python filter.py showing classified is_question and is_priority flags:
Instant Push Notifications & Webhook Debouncing
Alert production teams to priority audience questions without hitting rate limits.
Debounced Notifier
Aggregate high-priority chat messages and dispatch formatted rich embeds:
Paste terminal output from python webhook_notifier.py confirming alert sent with Status Code: 204:
SQLite Batch Buffering & Resilient Streaming Daemon
Buffer rapid chat messages in memory to prevent disk locking and automate 24/7 stream monitoring.
Batch Buffer & Storage
Use batch inserts with executemany to archive high-velocity chat streams effortlessly:
Run It Later: Continuous Live Stream Scraper Daemon
Run your broadcast scraper daemon with auto-reconnection across stream restarts:
Paste terminal output from initializing broadcast_chat.db:
Build Bot Better & Wipe Resistance
Apply profile and workspace protections so an agent cannot casually wipe your home folder or project data. Fleet rule: Hub conversation #31.
An autonomous agent running without boundary constraints executed a recursive delete targeting the user profile. Prompt rules and command-text deny lists (like rm or Remove-Item) fail when paths are passed inside variables or child scripts. BuildBotsBetter requires the complete defense trio: PreToolUse path inspection, off-volume backups, and a practised restore.
1. Per-Agent Onboarding Checklist (Run Once Per Agent)
Onboarding does not end when software installs. Generate and maintain a six-line checklist file for each agent operating on your system:
2. Variable-Limit Delete Guard Demo
Demonstrate why command-text pattern matching misses variable-derived deletions, while true path resolution catches and refuses them:
3. Off-Volume Profile & Data Backup
Back up chat message logs, sentiment aggregates, and token configurations off the OS volume:
4. Practised Restore Drill
Never trust an unverified backup. Run this safe, self-contained restore drill inside your temp folder:
5. Fail-Closed Workspace Policy
Lock output writing strictly to project directories. Never allow long-running scraping scripts or token refreshers to execute with unrestricted approval in the user home directory.
Paste terminal output from the restore drill or variable demo confirming protection: