How does this suite help my team verify code quality before a release?

The suite includes a master CLI runner that scans your local files against 25 specific engineering domains, providing an executive scorecard with pass/fail grades and prioritized remediation steps to ensure your code is production-ready.

Which AI agents and IDEs are compatible with these audit skills?

This suite is designed for technical leads and developers using agents like Claude Code, Cursor, or GitHub Copilot, providing deterministic checks that complement the creative output of those AI coding tools.

What exactly is included in the purchase?

You receive the `run_audit_suite.py` master runner, 25 individual audit scripts across five domains (AI, DevOps, Code Health, Security, Data), and comprehensive documentation including engineering checklists for each skill.

What are the technical requirements for running these audits?

The suite requires Python 3.8+ and performs heuristic analysis of local file structures and configurations; it does not require external API access to run the core audits, ensuring your codebase remains private.

Can these audits be used for official security or legal compliance certification?

While the suite provides high-signal engineering feedback on security and licensing, it is an automated heuristic tool and does not constitute formal legal advice or official compliance certification.

Codebase Audit & Production Readiness Suite

Example session with this skill installed

Use the codebase-audit-suite to run the production readiness audit on this repository.

Read your context and instructions
Compiled the codebase audit

Summary

Two real runs of the shipped scripts. Neither is a customer result.

1. Whole suite on a bare repo. run_audit_suite.py was run on the small sample-todo-cli fixture (no CI, no Dockerfile, no tests directory layout the audits look for). It scored

13/100, NOT READY: 0 audits passed, 1 warning, 24 failed, each with the missing artifacts listed.

python3 run_audit_suite.py --project fixtures/sample-todo-cli

2. One skill on a passing example. ai-rag-production-audit was run on the example manifest included in the package and returned

PASS, score 100, 8 files checked.

python3 skills/ai-rag-production-audit/scripts/audit_project.py \
  --manifest skills/ai-rag-production-audit/examples/pass_input.json

What this tells you

The audits check for the presence of expected files and keywords (for example evals, tests, config). They are fast heuristics, not a substitute for builds, tests, security scanners or human review.

Next steps

Run the suite on your repo, work through the prioritized missing-artifact list, and re-run.

Connects securely to your tools. The creator never sees your data.

About this skill

25 production readiness & security audit skills for engineering teams

Stop guessing whether a project is ready for production. This suite audits your codebase across five critical engineering domains using a single master runner (python3 run_audit_suite.py --project <path>) or 25 targeted Agent Skills.

Who this is for: technical leads, architects, and engineering teams using coding agents (Claude Code, Cursor, Codex, OpenCode) who need deterministic pre-release checks.

What you get

AI Engineering & Agents (5 skills): tool contract design, evals testset generation, LLM observability readiness, prompt-to-tool promotion, and RAG production audit.
DevOps & Cloud (5 skills): cloud deploy readiness, Docker productionization, environment and logging audit, GitHub Actions CI repair, and release automation.
Code Health & Quality (5 skills): CLI quality audit, FastAPI production readiness, Python package health, React project health, and TypeScript monorepo health.
Security & Compliance (5 skills): API key permissions, dependency risk audit, license/notice packaging, release readiness review, and secret leakage audit.
Data Pipelines (5 skills): business report generation, CSV/Excel cleaning, dashboard delivery, DuckDB/Polars analytics, and data quality gates.
Master Runner: run_audit_suite.py generates an executive scorecard with pass/warn/fail grades and prioritized remediation steps.

Read before you buy

Requires Python 3.8+.
Audits inspect local file structures, configuration, and patterns. They provide heuristic engineering signals, not formal legal or compliance certification.
Each skill includes documentation, checklists, and standalone execution scripts.

How to use

Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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Codebase Audit & Production Readiness Suite