claude

project-workflow

One-shot setup for a new repo's standards: feat → dev → main promotion model with a PR CI gate, GitHub repo setup (branch protection, deploy environments, required reviewers, environment-scoped OIDC), and the language-agnostic quality stack (lefthook hooks + a shared justfile, run identically in CI). The /project-init skill detects current state and applies only the missing patterns — on new repos and existing ones alike, plus an on-ramp for multi-repo workspaces (scaffold a coordination repo via feature-init --workspace). Setup-only and disposable: the evergreen standards live in the engineering-standards and quality-workflow plugins, pulled in as dependencies. Backed by lessons from real incidents.

14 on GitHubby Court Schuettv0.2.1updated 1 month ago
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Plugin project-workflow from marketplace schuettc-claude-code-plugins in schuettc/claude-code-plugins. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (4)

  • branch-promotion-model

    Use when bootstrapping a new repo's CI, setting up deploy workflows, deciding what branch a feature PR should target, or whenever someone proposes "auto-deploy prod on every main merge". Captures the feat → dev → main promotion model with separate Deploy Dev (push to dev) and Deploy Prod (push to ma

  • github-repo-setup

    Use when bootstrapping a new repo's GitHub-side setup — branch protection / rulesets, deploy environments, environment secrets, OIDC cloud auth, or required reviewers — or whenever deploy workflows reference secrets.* / environment: that don't exist yet. Captures the repo settings that make the feat

  • project-init

    Apply project-workflow standards to a repo — feat → dev → main promotion model + CI gate, GitHub repo setup (branch protection, environments, secrets, OIDC), and the quality stack (skylos/fallow via lefthook + a shared justfile, run identically in CI). Detects current state and applies only the *mis

  • quality-stack-setup

    Use when setting up a repo's lint / static-analysis / test tooling — wiring lefthook git hooks (pre-commit auto-fixers + pre-push full verify) and a justfile that is the single source of truth both the hooks and CI call, so local checks and CI can't drift. Language-agnostic: ruff/skylos for Python,

View source on GitHub

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Evergreen engineering standards I hold code to — the judgment layer that AI-slop resistance needs on top of the mechanical quality stack. Project-structure conventions (consistent layout + naming so every repo looks the same), worktree isolation (every line of work in its own tree so parallel work never collides), and GitHub API discipline (zipball over per-file, rate-limit backoff), with automation-auth (GitHub App vs PAT) and hook-escape conventions on the way. Pure advisory skills that fire when the situation matches — no tooling, no setup, safe to leave enabled for a project's whole life. Backed by lessons from real incidents.

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Sister to feature-workflow for code-quality findings. Surfaces, triages, and resolves static-analysis output (skylos for Python, fallow for TS/JS) with the same backlog-and-epic discipline. User-invocable skills: /quality-verify-hook self-tests pre-commit hooks against known-bad fixtures (catches the silently-misconfigured-hook class of bug), /quality-audit produces fingerprinted snapshots + NEW/RESOLVED/PERSISTING delta (suppressed findings excluded from active counts), /quality-unblock triages failing hooks with playbook-driven fix/suppress/defer proposals and refuses bare suppressions. Plus the language-agnostic suppression-discipline standard (every ignore carries an inline rationale). Day-1 playbooks for 13 skylos + 12 fallow rule_ids.

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Maintain project-workflow?

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claude & codex plugins7 plugins