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Workflow Playbook
Build reliable regular expressions by learning syntax, testing matches, visualizing structure, previewing replacements, benchmarking alternatives, and scanning for ReDoS risk.
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A regular expression often starts as a quick pattern, but production use needs more evidence. The same regex may validate form input, parse logs, drive a search-and-replace migration, feed a scraper, or gate a security rule. This workflow keeps that lifecycle together so you can move from design to verification without losing the original examples.
Start with regex-cheat-sheet when the syntax or flags are uncertain. If the source pattern began as a file glob, convert it with glob-to-regex before editing it by hand. Use ai-regex-explainer and regex-railroad-diagram-visualizer to make groups, alternation, lookarounds, anchors, and repetition visible enough for review.
Once the intent is clear, use regex-tester for expected matches and misses. Move to regex-debugger when the match path is surprising, and use named-group-tester when downstream code depends on extracted fields. If several rules need to run over the same text, multi-pattern-matcher helps compare coverage and overlap before the pattern set is accepted.
For replace workflows, preview substitutions with regex-replace-previewer so capture references do not silently corrupt text. Generate fixtures with regex-to-string-generator when tests need more valid examples. Before delivery, run regex-linter, compare alternatives with regex-benchmark, and scan final candidates with redos-regex-scanner. A good handoff states the dialect, flags, examples, replacement behavior, and remaining risk.
Workflow playbook
Start with syntax reference, glob conversion, AI explanation, and structural diagrams so the pattern's anchors, groups, alternation, and repetition are understandable before it is tested.
Run the pattern against realistic text, step through confusing failures, inspect named captures, and compare multiple candidate patterns against the same evidence.
If the regex will change text or feed tests, preview replacements with capture references and generate valid example strings to expand fixtures without inventing cases by hand.
Lint the final candidates, benchmark realistic and near-miss inputs, and scan for catastrophic backtracking before accepting the pattern for validation, parsing, search, or security rules.
Use reference, conversion, explanation, and visualization tools while designing. Move to testers, named-group checks, replacement preview, linting, benchmarking, and ReDoS scanning when the pattern must be trusted downstream.
Use testers, debuggers, and capture-group tools for correctness. Use the linter, benchmark, and ReDoS scanner when the pattern can match but may be too slow, ambiguous, or dangerous on near-miss input.