| Link Manager Protocol Version (LMP) | LMP Hex | Bluetooth Core Specification |
|---|---|---|
| LMP 0 | 0x00 | Bluetooth Core Specification 1.0b |
| LMP 1 | 0x01 | Bluetooth Core Specification 1.1 |
| LMP 2 | 0x02 | Bluetooth Core Specification 1.2 |
| LMP 3 | 0x03 | Bluetooth Core Specification 2.0 + EDR |
| LMP 4 | 0x04 | Bluetooth Core Specification 2.1 + EDR |
| LMP 5 | 0x05 | Bluetooth Core Specification 3.0 + HS |
| LMP 6 | 0x06 | Bluetooth Core Specification 4.0 |
| LMP 7 | 0x07 | Bluetooth Core Specification 4.1 |
Discover gists
| #!/usr/bin/env bash | |
| shopt -s nullglob | |
| lastgroup="" | |
| for g in `find /sys/kernel/iommu_groups/* -maxdepth 0 -type d | sort -V`; do | |
| for d in $g/devices/*; do | |
| if [ "${g##*/}" != "$lastgroup" ]; then | |
| echo -en "Group ${g##*/}:\t" | |
| else | |
| echo -en "\t\t" |
| # Converts Flipper SubGhz RAW Files to PSCustomObject[] | |
| function ConvertFrom-SubGhzRAW { | |
| param( | |
| [Parameter(Mandatory = $true, Position = 0, ValueFromPipeline = $true)] | |
| [String] $Path | |
| ) | |
| process { | |
| $data = Get-Content $Path | |
| if(!$data.Contains("Filetype: Flipper SubGhz RAW File")) { |
| #!/bin/bash | |
| for d in $(find /sys/kernel/iommu_groups/ -type l | sort -n -k5 -t/); do | |
| n=${d#*/iommu_groups/*}; n=${n%%/*} | |
| printf 'IOMMU Group %s ' "$n" | |
| lspci -nns "${d##*/}" | |
| done; |
| #!/bin/sh | |
| # SPDX-FileCopyrightText: 2017-2024 SanderTheDragon <sanderthedragon@zoho.com> | |
| # | |
| # SPDX-License-Identifier: MIT | |
| arch=$(dpkg --print-architecture) | |
| echo "Detected architecture: $arch" | |
| case "$arch" in |
Over the last few months, projects like Gas Town by Steve Yegge and OpenClaw by Peter Steinberger have made “AI agent orchestrators” feel suddenly mainstream. It is tempting to treat them as a new kind of intelligence, but under the hood they are still a small set of primitives wired together with discipline: an LLM API call, a state loop, tools, memory, and orchestration.
This raises a practical question: what is actually inside an “agent,” and how is it different from ChatGPT (a chat UI over a model) or coding tools like Claude Code (an agentic coding surface)? Gas Town’s README frames it as a “multi‑agent orchest
Welcome to St. Jude's Google Summer of Code 2026 homepage! With any questions, feel free to reach out to us via email at clay.mcleod@stjude.org and stephanie.sandor@stjude.org. Please include [GSoC] in the subject line.
If you do apply, please be sure to use our Application template!
apk add nano
nano /etc/apk/repositories
Uncomment the line "http://sjc.edge.kernel.org/alpine/vX.XX/community" where X.XX is the current stable number
| # Tasks definition | |
| # Tasks represent code or programs to be executed with the required parameters | |
| # Usage rules: | |
| # 1. Variables MUST NOT be made of other variables. This should be handled within the service integration | |
| # Implementation rules: | |
| # 1. Tasks MUST call at least one service | |
| # 2. Tasks MUST produce a result | |
| # 3. Tasks result object has 3 sub-objects: | |
| # the result code(integer), the execution log artifact (URL), the pipeline artifacts (URL) |
| import AVFoundation | |
| import VideoToolbox | |
| class H264Coder { | |
| var session: VTCompressionSession? | |
| var onFrame: ((CMSampleBuffer) -> Void)? | |
| let outputCallback: VTCompressionOutputCallback = { refcon, sourceFrameRefCon, status, infoFlags, sampleBuffer in | |
| guard let refcon = refcon, |
