Anti-hallucination: Linters and Hooks

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One of the challenges with AI code generation is preventing hallucinations - when the AI generates code that looks plausible but doesn't actually work. The solution? Use linters and hooks to catch errors before they become problems.

Here's the powerful pattern: run a linter after every edit. When Claude makes a change to your code, immediately run your linter - whether that's ESLint for JavaScript, Pylint for Python, or whatever tool your project uses. If the linter finds an error, Claude sees that error and can fix it immediately.

This creates a feedback loop. Claude makes an edit, the linter checks it, and if there's a problem, Claude sees the linter output and corrects the issue. It's like having a safety net that catches mistakes in real-time.

The key is setting this up as a hook - an automatic process that runs after every edit. You don't have to remember to run the linter manually, it just happens. And because Claude can see the linter output, it learns from its mistakes and adjusts its approach.

This dramatically reduces hallucinations because the AI gets immediate, concrete feedback about what works and what doesn't. Instead of generating potentially broken code and moving on, it generates code, checks it, and fixes any issues right away.

It's one of the most effective techniques for ensuring code quality when working with AI assistants.