[DEPRECATED] Build watchdog — launches arbitrary commands from the user message in tmux and lets sub-agent auto-apply a fix. Disabled pending the E5 bounded sub-agent contract + Jinja sandbox + side-effect ledger (plan §3.1 A1/A8 / §5.3 E4): the launch task interpolates raw user_message into a shell-bound tmux session and the heal step lets sub-agent mutate state with no rollback. Do not re-enable without `metadata.opensquilla.risk: high` + capabilities {shell, tmux, filesystem-write, subprocess} and a saga-style compensation step.
| Publisher | TokenRhythm |
| Repository | opensquilla |
| Skill name | meta-long-running-build-watchdog |
| Stars | 7K |
| Forks | 566 |
| Bundled files | Instructions only |
| License | Apache-2.0 |
| Links |
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Everything the model needs lives in the instructions — no extra files to sync.
Published by TokenRhythm on GitHub. Read the source before you install it.
Install the Meta Long Running Build Watchdog AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.
TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.
Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.
git clone --depth 1 https://github.com/TokenRhythm/opensquilla.git /tmp/opensquilla
mkdir -p .claude/skills
cp -r /tmp/opensquilla/src/opensquilla/skills/exp/meta-long-running-build-watchdog .claude/skills/meta-long-running-build-watchdogEnable Meta Long Running Build Watchdog in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.
AI skills are plain Markdown instructions rather than provider-specific code, so Meta Long Running Build Watchdog is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.
This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.
Watches a long-running command via tmux, lets sub-agent diagnose
failures and propose a fix, and records the diagnosis to memory.
Designed for overnight model fine-tunes, CI image builds, or repeated
regression suites that may fail intermittently.
Manually start a tmux session, scrape output, ask the LLM to diagnose, record the resolution.
[DEPRECATED] Build watchdog — launches arbitrary commands from the user message in tmux and lets sub-agent auto-apply a fix. Disabled pending the E5 bounded sub-agent contract + Jinja sandbox + side-effect ledger (plan §3.1 A1/A8 / §5.3 E4): the launch task interpolates raw user_message into a shell-bound tmux session and the heal step lets sub-agent mutate state with no rollback. Do not re-enable without `metadata.opensquilla.risk: high` + capabilities {shell, tmux, filesystem-write, subprocess} and a saga-style compensation step.
Because you install it once and use it with any model. Meta Long Running Build Watchdog is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.
Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/TokenRhythm/opensquilla/tree/main/src/opensquilla/skills/exp/meta-long-running-build-watchdog. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.
Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.
As many as you like. As long as a model supports skills, you can use Meta Long Running Build Watchdog with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.
Yes. It is published on GitHub by TokenRhythm under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.
An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.
A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.
Test Driven Development
Use when implementing any feature or bugfix, before writing implementation code
Using Git Worktrees
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - ensures an isolated workspace exists via native tools or git worktree fallback
Using Superpowers
Use when starting any conversation - establishes how to find and use skills, requiring skill invocation before ANY response including clarifying questions
Verification Before Completion
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence…
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