release
The `/release` command automates semantic version bumping and GitHub release creation for the higgsfield-ai-prompt-skill repository. It validates the version argument against strict semantic versioning, checks CHANGELOG.md, regenerates the user guide and manifest via Python scripts, commits changes with a templated message, creates and pushes a git tag, and finally publishes a GitHub release with the user guide PDF attached. Use this command when preparing a new production release after confirming all validation checks pass and changelog entries exist.
mkdir -p ~/.claude/commands && curl -fsSL https://raw.githubusercontent.com/OSideMedia/higgsfield-ai-prompt-skill/HEAD/.claude/commands/release.md -o ~/.claude/commands/release.mdrelease.md
Walk through a release for version $ARGUMENTS (e.g. `/release 2.1.0`). If no version argument is provided, check CHANGELOG.md for the latest version and ask what the new version should be. Steps: 0. **Sanitize the version argument** — before using `$ARGUMENTS` in any shell command, confirm it is a bare semantic version matching `^[0-9]+\.[0-9]+\.[0-9]+$` (e.g. `2.1.0`). If it contains anything else (spaces, `;`, backticks, quotes, path separators), STOP and ask the user for a clean version string — never interpolate an unvalidated argument into the `git commit` / `git tag` / `gh release create` shell snippets below. 1. **Release gate** — run `python3 scripts/validate.py --strict`, `python3 -m pytest tests/ -q`, and `python3 scripts/validate.py --evals`. Stop if any of the three fails. 2. **Changelog check** — confirm CHANGELOG.md has an entry for this version. If not, ask what to add. 3. **Regenerate the user guide + manifest** — AFTER the frontmatter version/date are bumped: `python3 scripts/generate_user_guide.py`, then `python3 scripts/validate_user_guide.py` (manifest-fallback comparison; review any flagged drift), then `python3 scripts/validate_user_guide.py --write-manifest` and stage the refreshed `docs/user-guide/MANIFEST.json`. The PDF itself is a release artifact — it is git-ignored, never committed. 4. **Commit** — stage and commit any pending changes with message: `feat: v$ARGUMENTS — <summary from changelog>` 5. **Tag** — create git tag `v$ARGUMENTS` 6. **Push** — push commit and tag: `git push && git push --tags` 7. **GitHub release** — create release from the tag: `gh release create v$ARGUMENTS --title "v$ARGUMENTS" --notes-file -` using the changelog entry as notes. 8. **Attach the guide** — `gh release upload v$ARGUMENTS docs/user-guide/USER-GUIDE.pdf` so the PDF ships with the release instead of the git history. Confirm with the user before each destructive/visible step (commit, push, release).
>
Writes the character-performance layer of a video prompt as behavior under pressure, not displayed emotion — objective, obstacle, tactics, beats, subtext, listening, body/status/proxemics, and mandatory eye life. Produces a reusable 150–220-word acting master profile per character plus a per-scene rewrite of it, and a locked voice prompt. Use whenever a prompt needs acting, performance, or emotion direction; whenever characters read wooden, dead-eyed, or 'AI'; whenever a character must stay themselves across many shots; or when the user asks for character behavior, mannerisms, tics, a gait, or how someone reacts. Pairs with higgsfield-facs (muscle-level AU codes) and higgsfield-seedance (the prompt the paragraph goes into).
>
>
>
>
Use when the user mentions Higgsfield Canvas, a node-based or node graph workspace, an infinite board/canvas, chaining generations into a pipeline, or wants to wire prompts → images → videos across models on one surface. Covers what Canvas is, the node categories, the seven models that run inside Canvas, the named canvas patterns (Simple Seedance, Extend Video, Image Edit, StoryBoard With Elements, Long Video fan-out), the build-free / generate-paid cost model, reusable templates, assets-as-nodes, and Shared Canvas live collaboration. Also trigger on 'Higgsfield ComfyUI alternative', 'node workflow', or 'connect nodes to build a scene/campaign'.
Pre-production story-and-character development for Higgsfield projects — the upstream layer that decides WHAT to prompt before any model runs. Use when the user wants to build a character, design a world, develop a story or premise, create a character sheet / character bible / story bible, lock a visual style or 'visual DNA', plan a multi-shot narrative with consistent characters, or says things like 'help me design a character', 'build the world', 'I need a backstory', 'make this character consistent across shots', 'develop my film/series concept', or 'I keep getting generic AI characters'. Routes the locked outputs into higgsfield-prompt + the right model. Adapted from Higgsfield's official character-design framework by @vavavinca.