Check gender-neutral language

Matching is case-insensitive and whole-word, multi-word phrases take priority over shorter substrings, and empty mappings are rejected with invalid_input so a blank glossary cannot masquerade as a clean report. Use it free in the browser while drafting, or call the API at $0.002 per successful request when CI, CMS hooks, or editorial tooling need the same flags every time.

What the gender-neutral language check reports and how matches are counted

The response echoes the source text, reports mapping_size as how many unique terms were loaded after deduplication, match_count as the total number of occurrences found, flagged_count as how many distinct terms appeared at least once, and flags as a ranked array of term, neutral, count, positions, and the first surface form matched. Terms present in the mapping but absent from the text simply do not appear in flags; a clean passage returns an empty flags array with match_count zero rather than an error. Empty text, whitespace-only paste, missing mapping, empty mapping arrays or objects, rows with blank terms or blank neutrals, oversized payloads, and non-string bodies are rejected with invalid_input.

How the text and mapping fields are read and how results stay reproducible

The value must be a non-empty string after a meaningful content check; finite numbers and bigints are stringified first so a bare identifier typed as a number still produces a stable character sequence. Empty arrays, empty objects, and missing mapping fields fail with a message that states at least one pair is required—the hard rule behind this capability. Each row is trimmed; blank terms or blank neutrals after trim are rejected by index so authors can fix the bad row without guessing. Duplicate term keys keep the first definition for a stable contract. Internally the engine sorts longer terms first, builds a covered-range mask so overlapping hits from shorter terms are skipped after a longer phrase claims those characters, and records zero-based character positions for every accepted match. The preferred text field is text, but aliases input, string, value, content, and s are accepted so query strings, spreadsheets, and typed forms can reuse the same contract without renaming columns. Booleans, plain objects, and arrays are rejected with a clear message so a mistaken JSON body does not become the word true or an unhelpful object dump. Empty string and whitespace-only paste are always invalid_input: the product promise is check gender-neutral language against a real passage, not invent a silent success for a blank submit. Length is capped at one hundred thousand characters so a runaway paste cannot monopolize a Worker; longer payloads fail with an explicit limit message rather than a truncated silent cut. The preferred mapping field is mapping, with aliases terms, glossary, replacements, and map. It must be a non-empty array of objects each containing term and neutral strings, or a non-empty plain object whose keys are gendered terms and whose values are neutral strings. Pair the free browser run on this page with the priced API when you need the identical report inside an automated pipeline or editorial CMS.

Where gender-neutral language checks fit in writing, teaching, and software

Policy and compliance reviewers attach the JSON report to change tickets as evidence that a document was scanned with a documented map before release. On this page the work runs entirely in your browser; through the API each successful analysis costs $0.002, failed validation is not charged, and nothing is stored after the response returns. That split—free interactive exploration and a priced, identical API—matches the rest of the KIT tier-A catalog and lets you move from a style-guide workshop to an automated pipeline without changing the numeric result.