This document provides guidelines for maintaining high-quality Python code. These rules MUST be followed by all AI coding agents and contributors.
All code you write MUST be fully optimized.
"Fully optimized" includes:
Claude Flow treats memory as the backbone and MCP tools as the hands. You get concurrent agents that coordinate cleanly, keep context tight, and ship durable artifacts without dragging long text through prompts. It feels like an ops layer for intelligence.
The stack is simple. Claude Code as the client. Claude Flow as the MCP server. SQLite memory at .swarm/memory.db for state, events, patterns, workflow checkpoints, and consensus. Artifacts hold the big payloads. Manifests in memory link everything with ids, tags, and checksums.
Coordination is explicit. Agents write hints to a shared blackboard, gate risky steps behind consensus, and record every transition as an event. Hooks inject minimal context before tools run and persist verified outcomes after. Small bundles in, durable facts out.
Planning keeps runs stable. Use GOAP to sequence actions with clear preconditions. Use OODA to shorten loops.
Observe metrics, orient with patterns, decide through votes, act with orchestration. Topology adapts from hi
| # from: <https://x.com/iannuttall/status/1965090297630826931> | |
| cdx() { | |
| if [[ "$1" == "update" ]]; then | |
| npm install -g @openai/codex@latest | |
| else | |
| codex -m gpt-5-codex --yolo -c model_reasoning_effort="high" -c model_reasoning_summary_format=experimental --search "$@" | |
| fi | |
| } | |
| # Note: with auto confirmation. use at your own risk. thanks! |
| if(-Not $cursorPath -OR -NOT $appDataCursorPath){ | |
| Write-Host "set `$cursorPath with the actual installation path of Cursor" | |
| Write-Host "set `$appDataCursorPath with the actual installation path of Cursor" | |
| } | |
| Write-Host "Remove $cursorPath and it's contents" | |
| if (Test-Path $cursorPath) { | |
| Remove-Item -Recurse -Force $cursorPath | |
| } | |
| #!/bin/bash | |
| # Define variables | |
| APPIMAGE_PATH="/opt/cursor.appimage" | |
| ICON_PATH="/opt/cursor.png" | |
| DESKTOP_ENTRY_PATH="/usr/share/applications/cursor.desktop" | |
| # Determine the shell and RC file | |
| SHELL_NAME=$(basename "$SHELL") |
A step-by-step guide to setting up Model Context Protocol (MCP) servers for Claude Desktop on Windows.
node --versionnpm --version
While it's possible to stream most content to Apple Vision Pro directly over the internet, having the ability to use Apple Vision Pro as an HDMI display can still be useful.
Since Apple Vision Pro does not support connecting to an HDMI input directly or using an HDMI capture card, we have to be a little creative to make this work. NDI provides the ability to stream HDMI content over a local network with really low latency, and it works great with Apple Vision Pro.
This page shows the setup I’m using.
| # - Create CreateScheduledTask.ps1 file with content below. | |
| # - Run as admin command in PowerShell: | |
| # Get-Content .\CreateScheduledTask.ps1 | PowerShell.exe -noprofile - | |
| # - Restart Windows | |
| # - Launch WSL | |
| # - Launch VPN | |
| # - Done! Metric automatically updated | |
| $taskname="Fix VPN for WSL" | |
| $scriptName = "UpdateAnyConnectInterfaceMetric.ps1" |