Run a fixed 7-step CI quality gate sequence with auto-fixes.
npx skills add https://github.com/ByronWilliamsCPA/.claude --skill ci-fix-byronwilliamscpa
Please help me install this Agent Skill. Skill: ci-fix Source: https://github.com/ByronWilliamsCPA/.claude/tree/main/.claude/skills/ci-fix Command: npx skills add https://github.com/ByronWilliamsCPA/.claude --skill ci-fix-byronwilliamscpa
Manually running sequential CI quality gates, troubleshooting failures, and re-running checks after fixes is time-consuming and error-prone, often leading to missed steps or incomplete validation before commit. This skill automates the entire 7-gate CI sequence, handles auto-fixes for resolvable issues, and clearly surfaces blockers that require manual intervention.
Use the ci-fix skill to run all CI quality gates for your project, auto-fix any resolvable issues, and check if your code is ready to commit.
High-intent search queries and answers about installing and using this skill.
Automated CI validation runs a fixed 7-step quality gate sequence covering formatting, linting, testing, security scanning, and dependency audits to ensure consistent, repeatable validation with deterministic auto-fixes and clear blocker reporting.
The best way to automate Python code quality checks is using a sequential CI pipeline that runs ruff format, ruff lint, qlty check, pre-commit, pytest, bandit, and pip-audit in a fixed, non-skippable order to ensure consistent validation.
Yes, the auto-fix CI gate sequence supports security scanning and dependency audits by running bandit for security scanning and pip-audit for dependency checks, marking persistent failures as blockers that require manual intervention.
For CI pipeline failures that cannot be auto-fixed, the sequence provides a real-time status table for all gates, marks persistent failures as blockers requiring manual intervention, and only offers to commit when all required gates pass.
This CI validation workflow is specifically designed for Python software development pipelines where CI fails on formatting, linting, testing, security scanning, or dependency audit checks, applying Python-specific tools like ruff, pytest, and pip-audit.
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