Utility Store

Wrap string fields in localization objects while keeping the result as structured JSON

Compute rollups and summary metrics over arrays such as count, sum, average, unique values, and flatten

Clean noisy JSON by removing nulls, empties, duplicates, and other low-value clutter

Create derived values or fields from formulas, expressions, and simple conditionals

Enforce expected source-shape requirements before a pipeline transforms data

Copy, move, or swap values between known JSON paths without broad restructuring

Parse CSV text into a JSON array of row objects for further cleanup or reshaping

Combine two object trees into one with configurable deep-merge conflict resolution

Compare two JSON inputs and return a structured diff of what changed

Add or default fields on objects using expressions, generated values, and fallbacks

Convert objects to key-value entry arrays or rebuild objects from entries

Filter rows, items, keys, or values by explicit conditions and keep only the matches you want

Find and replace matching keys or values across JSON using broad search patterns

Convert nested objects to flat key paths or rebuild them using delimiter and casing rules

Reformat individual values with case changes, trimming, coercion, and slugification

Generate mock JSON data from a template for testing, demos, or seeding pipelines

Convert JSON array row data into final CSV text output

Remap existing values through a lookup table such as enums, codes, or category names

Enforce a consistent schema across array items by filling missing keys and removing extras

Parse browser DevTools console text into a structured JSON array of console entries

Parse Named Debug Structured log lines into structured JSON records

Keep only a known allowlist of fields and remove everything else

Mask secrets and PII while keeping the surrounding JSON structure intact

Remove known fields, paths, or matching keys from JSON without masking the values

Rename known keys or convert key casing without changing the underlying values

Flexibly restructure collections by grouping, unwinding, transposing, or rearranging nested data

Enforce a known target shape by extracting paths, ensuring arrays, unwrapping values, or plucking indices

Summarize a payload with compact statistics, structural overviews, and anomaly signals

Shape tabular JSON rows with spreadsheet-like operations before later transforms or export

Reduce oversized payloads by truncating strings, capping arrays, and dropping large blobs