From codescene
Gates AI-generated code changes with Code Health reviews before commit, handoff, or pull request to catch maintainability regressions.
How this skill is triggered — by the user, by Claude, or both
Slash command
/codescene:safeguarding-ai-generated-codeThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Use Code Health safeguards before declaring AI-touched code ready. The goal is to catch maintainability regressions early and prevent agents from normalizing technical debt.
Use Code Health safeguards before declaring AI-touched code ready. The goal is to catch maintainability regressions early and prevent agents from normalizing technical debt.
Do not use this skill for broad refactoring discovery or project-level prioritization.
code_health_review: Review each AI-modified file immediately after the change.pre_commit_code_health_safeguard: Check staged or modified files before commit.analyze_change_set: Check a branch or PR-style change set against a base ref.code_health_review on that file.pre_commit_code_health_safeguard before commit-oriented recommendations as a broader gate across staged or modified files.analyze_change_set before PR-oriented recommendations as a final branch-level gate.code_health_review and keep iterating until the issue is removed or the user explicitly accepts the risk.npx claudepluginhub codescene-oss/codescene-mcp-server --plugin codesceneProvides real-time structural code health scores via CodeScene MCP — review maintainability before edits, verify score deltas after changes, gate commits and PRs.
Polishes code changes before PR by recovering branch context, checking against codebase guidelines for changed files, removing AI slop like extra comments and casts, and final review.
Conducts multi-axis code reviews evaluating correctness, readability, architecture, security, and performance before merging changes.