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Deploy the application to staging or production and roll back failed releases
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Basé sur la classification professionnelle SOC
Create a Pull Request for the current branch
Review an open PR before approving it
Analyze upstream specs (agentskills.io, Claude Code plugin/marketplace format, OpenClaw, MCP, CodeRabbit, APM) for changes, identify gaps in skillsaw's rule coverage, and create or update PRs to close those gaps. Use when performing periodic maintenance on the skillsaw linter.
Create a skillsaw rule plugin — a pip-installable Python package that adds custom lint rules to skillsaw. Walks through scaffolding the package, writing rules against the lint tree, testing, and publishing to PyPI. Use when a user wants to share skillsaw rules across repositories or publish them for others.
Survey the AI coding assistant and agentic tool ecosystem, assess skillsaw's competitive position, identify emerging patterns and missing capabilities, and produce a prioritized strategic report as a GitHub issue.
Fix skillsaw lint violations — apply deterministic autofixes, then resolve the remaining violations with targeted edits guided by `skillsaw explain`. Use when skillsaw reports violations, when asked to clean up lint findings, or after `skillsaw fix` leaves violations behind.
| name | deploy |
| description | Deploy the application to staging or production and roll back failed releases |
Run deployments from a clean working tree on the main branch.
make deploy ENV=staging
make deploy ENV=production
## Rollback
Try to roll back immediately when a release fails health checks. Ideally
the pipeline reverts bad releases on its own, but if possible verify the
dashboards yourself after every deploy.