deploy
SkillCloud & infraDeploy any branch to its HF Space directly from the CLI (local, no push) and monitor until the Space is live.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the deploy skill
What this skill tells your AI
The instructions your AI receives, as published by qud-technologies/quranic-universal-audio in .claude/skills/deploy/SKILL.md and read by ahel’s review.
Deploy the Inspector to its Hugging Face Space straight from the current checkout — no git push, no GH-Actions runner. The deploy stages the git-tracked tree, uploads it to the Space repo, and factory-reboots the Space, so it reflects the committed state of whatever branch/worktree you run it from. Default target is the dev Space; pass prod to target prod.
Run
-
Deploy (foreground, ~15-30s to upload + trigger the rebuild):
bash .claude/skills/deploy/scripts/deploy.sh dev -
Monitor readiness as a background Bash job (
run_in_background: true) so you're notified when the Space is actually live — it polls the HF Space runtime stage untilRUNNINGand/healthzreturns 200, not just when the upload finished:python .claude/skills/deploy/scripts/wait_space.py devExits 0 when RUNNING + healthy, non-zero on
BUILD_ERROR/RUNTIME_ERROR/ a paused-or-stopped Space / timeout.
Notes
- Local — no remote branch required. It stages the tracked files of the checkout you run it from; run it from the worktree on the branch you want live. Untracked files are not staged.
- Targets:
dev→hetchyy/quranic-inspector-dev,prod→hetchyy/quranic-universal-audio. - CI path instead (runs the full check suite, deploys a pushed ref):
gh workflow run inspector-deploy.yml --ref <branch> -f env=dev.
Signals
- GitHub stars
- 33
- Forks
- 4
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
deploy-qud-technologies- Source
- github.com/qud-technologies/quranic-universal-audio
github.com/qud-technologies/quranic-universal-audio