What we are building
AI Code Verify brings together a small, usable code checker and practical guides to a broader verification workflow. The starting point is a simple question: what evidence supports a decision to trust a change?
The current tool checks a pasted JavaScript, TypeScript or Python snippet locally in the browser. It reports syntax diagnostics and selected fixed-rule findings with their sources and locations. It does not execute the submitted program or send the snippet to an AI model.
Our guides cover the work that a snippet checker cannot do: defining expected behavior, reviewing the actual diff, running independent tests, examining callers and dependencies, and deciding which checks belong in a project’s delivery process.
The product scope is specific. This release does not scan repositories, run tests, connect to pull requests or prove correctness. “Large scale code verification” describes the wider engineering task explored in our guides, rather than a claim that the local tool understands a complete codebase.
Who publishes the site
AI Code Verify is the project name and the organization byline used for the site’s editorial content. The byline identifies this independent publishing project. We do not list invented reviewers, professional credentials, customers or advisory boards.
Product and engine names belong to their respective owners. References to Babel, Ruff, Cursor, Claude Code or other tools help explain a workflow or source; they do not indicate a partnership or vendor endorsement.
Our editorial standard
- Start with primary sources. Link to official documentation, source repositories and original research where possible. Recheck claims that depend on product versions or deployment options.
- Separate documentation from demonstration. “The documentation says” and “we ran this example” are different claims. A documented capability is not an independently measured detection rate.
- Keep test conditions visible. Examples should identify their input, relevant rule and expected finding. Broader measurements need their dataset, configuration, versions and limitations before they can be called a benchmark.
- Describe what was not checked. Skipped rules, omitted context, failures and no-findings results should remain visible. A green status must not become a promise that code is safe.
- Use narrow recommendations. Explain which task a tool or workflow addresses. Avoid universal rankings based on unrelated vendor benchmarks, marketing percentages or a single example.
- Make corrections traceable. Review reproducible reports, correct inaccurate claims and update the affected page when its substance changes.
The tool’s technical foundation
JavaScript and TypeScript use the Babel parser and four custom AST rules. Python uses the official Ruff WebAssembly package with a fixed list of selected rules. The static analysis page publishes the running engine versions, enabled rule IDs and known limits, including Python’s inline # noqa behavior.
These dependencies keep their own open-source licenses and attribution. The custom rules and the interface should be evaluated by what they actually check, rather than by the total capability of the upstream engines.
Privacy and sustainable scope
Keeping submitted code in the browser removes the need to upload it to a scanning server for this release. There are no user accounts, paid plans or AI review requests in the checker. Optional page analytics are separate and load only after permission. Hosting and asset requests still involve normal network delivery; the privacy notice explains that distinction.
Future features depend on a demonstrated user need and a clear operating model. A proposed integration or workflow described in a guide should not be read as a feature already available in the product.
Corrections and contact
For an inaccurate explanation, broken page or reproducible tool problem, use the contact page. Include the page URL, language, rule ID and a minimal synthetic example if possible. Please remove credentials, proprietary code and personal information before sending an email.