Cuts a git release end-to-end: clean tree, push, tag, release notes, deploy.
npx skills add https://github.com/ledtorch/coding-agent-workflow --skill release-ledtorch
Please help me install this Agent Skill. Skill: release Source: https://github.com/ledtorch/coding-agent-workflow/tree/main/skills/release Command: npx skills add https://github.com/ledtorch/coding-agent-workflow --skill release-ledtorch
git add -A. - Structured release notes: Generates a title plus a markdown body with a stat line, fixed emoji theme sections, and claim-evidence bullets derived from the git log between tags. - Use Case: Run /release v1.2.0 after finishing a milestone; the Skill commits pending work, pushes main, creates and pushes the annotated tag, drafts GitHub release notes, and offers a dry-run then real deploy via deploy.sh. ## Quick Start Run the release skill with a tag name like /release v1.2.0 to clean the tree, push, tag, generate release notes, and deploy.High-intent search queries and answers about installing and using this skill.
Invoke the release command with an explicit tag name, such as /release v1.2.0. The workflow runs preflight checks, cleans the tree through a commit proposal flow, pushes main, creates and pushes the annotated tag, generates release notes, and offers a deploy.
The notes are built from git log between the previous tag and the new one, with a derived stat line showing commit count and date range. Sections use fixed emoji themes, and bullets follow a bold claim plus evidence format naming real files and identifiers.
A dirty tree triggers the full commit workflow: changes are grouped by topic, commit messages are proposed, and the run waits for explicit approval. It never runs git add -A blindly, and uncommittable half-finished work stops the release with a report.
No. Preflight verifies the tag exists neither locally nor on the remote, and the workflow never re-tags, moves, deletes, or force-pushes. A rejected push from a diverged remote stops the run with a report.
No. Publishing the GitHub release and running the deploy both require explicit approval in the session. The deploy offers a dry-run first, and the result is only claimed after the deploy script's HTTP check returns success.
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