Generate entire projects from your terminal with AI

Built with Codex CLI?
Let's make sure it's production-ready.

OpenAI's terminal-based coding agent that generates full projects from natural language prompts directly in your terminal. Produces Python, TypeScript, React, and Node.js code with shell script automation. We help non-technical founders identify and fix the issues AI tools leave behind.

PythonTypeScriptReactNode.jsShell Scripts

Common issues we find in Codex CLI code

These are real problems we see in Codex CLI projects during our audits — not hypotheticals.

highSecurity

API keys and secrets written directly into generated source files

Codex CLI generates code with placeholder credentials that developers often replace with real values inline, leaving secrets committed to version control. There is no .env scaffolding or secret management setup by default.

highSecurity

No authentication or authorization on generated API endpoints

When Codex generates Express or FastAPI backends, routes are created without middleware for authentication, meaning every endpoint is publicly accessible immediately after deployment.

mediumCode Quality

Single-file output breaks apart for any real project structure

Codex frequently outputs all logic into one or two files rather than organizing code into modules, services, and utilities — making the result hard to maintain and extend as the codebase grows.

mediumBugs

Generated code lacks awareness of existing project context

Because Codex operates from a prompt without full codebase indexing, it generates code that duplicates existing utilities, ignores established conventions, and introduces conflicting patterns alongside your real code.

mediumDeployment

No dependency management or package.json / requirements.txt generation

Codex outputs code that imports packages without generating the corresponding dependency manifest, so the generated code fails immediately on a fresh install until dependencies are manually identified and added.

mediumBugs

Unhandled promise rejections and missing try/catch in async code

Generated async JavaScript and Python code handles the happy path but omits error handling for network failures, timeouts, and API errors, causing unhandled rejections that crash Node.js processes.

lowTesting

No test files generated alongside application code

Codex CLI produces application logic without corresponding unit or integration tests, meaning the output has zero test coverage by default and no testing framework configured.

mediumPerformance

Shell scripts generated without input sanitization or error exits

Generated shell scripts rarely include `set -euo pipefail` or input validation, so scripts silently continue after failures and are vulnerable to injection if they incorporate user-provided values.

Start with a self-serve audit

Get a professional review of your Codex CLI project at a fixed price. Results reviewed by experienced engineers.

Security Scan

Black-box review of your public-facing app. No code access needed.

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  • SSL/TLS analysis
  • Security headers
  • Expert review within 24h
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Code Audit

In-depth review of your source code for security, quality, and best practices.

$19
  • Security vulnerabilities
  • Code quality review
  • Dependency audit
  • AI pattern analysis
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Complete Bundle

Both scans in one package with cross-referenced findings.

$29$38
  • Everything in both products
  • Cross-referenced findings
  • Unified action plan
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100% credited toward any paid service. Start with an audit, then let us fix what we find.

How it works

1

Tell us about your app

Share your project details and what you need help with.

2

Get a clear plan

We respond in 24 hours with scope, timeline, and cost.

3

Launch with confidence

We fix what needs fixing and stick around to help.

Frequently asked questions

Is Codex CLI safe to use for production code at a startup?

Codex CLI is best treated as a rapid prototyping tool. The generated code requires security review before production use — in particular, check for hardcoded credentials, missing authentication on API routes, and lack of input validation. Plan for a review pass before shipping any Codex-generated backend code.

Why does Codex-generated code fail to run after I copy it into my project?

The most common reason is missing dependencies. Codex writes import statements without generating a package.json or requirements.txt, so you need to identify and install each package manually. Also check for path assumptions that only work in the directory where Codex was run.

Can Codex CLI generate tests for the code it writes?

You can prompt Codex to generate tests, but it does not do so automatically. Explicitly ask it to write unit tests for each function it generates. The quality varies — Codex tends to write tests that pass trivially rather than testing edge cases, so review the test logic carefully.

How does Codex CLI compare to Cursor or GitHub Copilot for a small team?

Codex CLI excels at greenfield code generation from the terminal without opening an IDE. Cursor and Copilot have better awareness of your existing codebase context. If your team works primarily in editors, Cursor or Copilot will integrate more naturally. Codex CLI is a strong fit for scripting, automation tasks, and generating standalone modules.

What is the best workflow for reviewing Codex CLI output before merging?

Generate Codex output into a separate branch, then do a focused code review covering: secrets and credentials, authentication gaps, missing error handling, and dependency correctness. Treat Codex output like a junior developer's first draft — the structure is often good, but the details need verification.

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