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- Claude Code Templates
- Production Code Audit
production-code-audit_skill
- Python
20.6k
GitHub Stars
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2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
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Installation
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npx veilstrat add skill davila7/claude-code-templates --skill production-code-audit- SKILL.md15.5 KB
Overview
This skill autonomously deep-scans an entire codebase, understands architecture and patterns, and transforms the project into production-grade, corporate-quality code. It finds security, performance, architecture, testing, and quality issues and applies systematic fixes and optimizations. The result is verified by tests, metrics, and a comprehensive before/after report.
How this skill works
The skill first discovers the codebase automatically by listing and reading files, detecting languages, frameworks, entry points, and data flow. It then performs line-by-line inspections to identify architecture problems, security vulnerabilities, performance bottlenecks, code-quality defects, and missing tests. Finally, it applies targeted fixes and refactors, adds production infrastructure (logging, monitoring, health checks), runs the test suite, and generates a metrics-backed report.
When to use it
- When you tell the agent to "make this production-ready"
- When you request a full codebase audit or enterprise hardening
- When preparing for production deployment or compliance reviews
- When optimizing for security, performance, or maintainability
- When test coverage and CI/CD need to be added or improved
Best practices
- Scan the entire repository recursively; do not skip files
- Prioritize and fix critical security and data-loss issues first
- Measure impact with before/after metrics (performance, coverage, vulnerabilities)
- Run full test suites after each change to avoid regressions
- Document every change and add deployment and monitoring guides
Example use cases
- Convert a prototype or MVP into a production-grade service with logging, monitoring, and CI/CD
- Automatically fix OWASP Top 10 issues and remove hardcoded secrets
- Refactor monolithic god classes, remove circular dependencies, and split responsibilities
- Resolve N+1 queries, add caching, and optimize database indexes for low-latency APIs
- Add comprehensive tests and increase coverage to enterprise targets
FAQ
The skill is designed to operate autonomously on invocation. Best practice is to run it on a branch or in a sandbox and review changes via diffs or pull requests.
How are fixes verified?
All changes are verified by running the project's test suite, static analyzers, and security scans. The skill reports before/after metrics for performance, coverage, and vulnerabilities.