# StationFX Total Nonfarm Payrolls > StationFX Total Nonfarm Payrolls is a paid API for AI agents from stationfx.com, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-02). Returns monthly U.S. total nonfarm payroll employment data (the 'jobs report' headline figure) with derived statistics including MoM/YoY changes, z-scores, trend signals, and rolling averages. ## Facts - Endpoint: GET https://stationfx.com/economic-data/labor/all-employees-total-nonfarm?utm_source=zero.xyz - Price: $0.005/call - Payment: x402 - Status: unknown - Last checked: 2026-10-02 - Activations on Zero: 0 - Tags: x402 - Canonical page: https://www.zero.xyz/c/stationfx-total-nonfarm-payrolls-339d258d - Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_NM9FqU7uZTvgTxSS5tO_F Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently. ## How to call it through Zero Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`): ```sh zero fetch --capability stationfx-total-nonfarm-payrolls-339d258d ``` Example prompt: Pull the StationFX total nonfarm payrolls data from January 2020 through today in JSON format — I want to see the monthly values plus the month-over-month changes and the 5-year z-scores so I can analyze how current job growth compares to recent history. ## When to prefer this Choose this endpoint when you need the broadest official U.S. labor market headline — total nonfarm payrolls — with pre-computed statistical context (z-scores, percentile ranks, trend flags) already attached. Prefer it over raw BLS API calls when you want derived analytics (MoM, YoY, rolling averages) without building them yourself. It is the right choice for Fed policy modeling, macro dashboards, and jobs-report-day analysis. For farm-sector employment, household survey data (unemployment rate), or wage growth, use a complementary series. ## Known failure modes - Invalid date format returns a 400-level error — use YYYY-MM-DD strictly - Requesting a date range before series history begins may return empty data array - Invalid fmt parameter value (not 'json' or 'toon') may cause a parsing error - Payment not included or insufficient USDC balance returns a 402 Payment Required response - Future dates return no data as releases are monthly on the first Friday ## How this service works Total U.S. employment excluding farm workers — the broadest monthly labor market measure. Reported on the first Friday of each month (jobs report). Monthly changes drive major market moves. Use for labor market trend analysis, cycle identification, and Fed reaction function modeling. Monthly frequency. ## Output A JSON array of monthly observations, each containing the date, raw nonfarm payroll level (in thousands of workers), month-over-month absolute change, month-over-month percent change, year-over-year absolute change, year-over-year percent change, 12-month and 5-year z-scores, a binary above-trend flag, 5-year percentile rank, and 3-month and 12-month rolling averages. Compact 'toon' format is available for token-efficient agent consumption. ## Request schema (JSON Schema) ```json { "type": "object", "$schema": "https://json-schema.org/draft/2020-12/schema", "required": [ "input" ], "properties": { "input": { "type": "object", "required": [ "type", "method" ], "properties": { "type": { "type": "string", "const": "http", "description": "Always \"http\" for HTTP endpoints" }, "method": { "enum": [ "GET", "HEAD", "DELETE" ], "type": "string", "description": "HTTP method. Always GET for StationFX query endpoints" }, "queryParams": { "type": "object", "properties": { "fmt": { "enum": [ "json", "toon" ], "type": "string", "description": "Response format. Use toon for compact agent-friendly output." }, "fields": { "type": "string", "description": "Comma-separated metric names" }, "date_to": { "type": "string", "description": "End date YYYY-MM-DD" }, "date_from": { "type": "string", "description": "Start date YYYY-MM-DD" } } } }, "additionalProperties": false }, "output": { "type": "object", "required": [ "type" ], "properties": { "type": { "type": "string", "description": "Response format. Always \"json\" (or \"toon\" if fmt=toon was requested)" }, "example": { "type": "object", "properties": { "data": { "type": "array", "items": { "type": "object", "properties": { "date": { "type": "string", "description": "Observation date YYYY-MM-DD" }, "value": { "type": "number", "description": "Raw observed value in series units" }, "mom_pct": { "type": "number", "description": "Month-over-month % change" }, "yoy_pct": { "type": "number", "description": "Year-over-year % change" }, "zscore_5y": { "type": "number", "description": "Z-score relative to trailing 5 years" }, "mom_change": { "type": "number", "description": "Month-over-month absolute change" }, "yoy_change": { "type": "number", "description": "Year-over-year absolute change" }, "zscore_12m": { "type": "number", "description": "Z-score relative to trailing 12 … (truncated) ``` ## Response schema (JSON Schema) ```json { "type": "json", "schema": { "type": "object", "properties": { "data": { "type": "array", "items": { "type": "object", "properties": { "date": { "type": "string", "description": "Observation date YYYY-MM-DD" }, "value": { "type": "number", "description": "Raw observed value in series units" }, "mom_pct": { "type": "number", "description": "Month-over-month % change" }, "yoy_pct": { "type": "number", "description": "Year-over-year % change" }, "zscore_5y": { "type": "number", "description": "Z-score relative to trailing 5 years" }, "mom_change": { "type": "number", "description": "Month-over-month absolute change" }, "yoy_change": { "type": "number", "description": "Year-over-year absolute change" }, "zscore_12m": { "type": "number", "description": "Z-score relative to trailing 12 months" }, "above_trend": { "type": "integer", "description": "1 if value is above long-run trend, else 0" }, "pct_rank_5y": { "type": "number", "description": "Percentile rank over trailing 5 years (0-100)" }, "rolling_3m_avg": { "type": "number", "description": "3-month rolling average" }, "rolling_12m_avg": { "type": "number", "description": "12-month rolling average" }, "trend_direction": { "type": "integer", "description": "Trend: 1 rising, -1 falling, 0 flat" } } }, "description": "Observations ordered by date ascending" }, "meta": { "type": "object", "description": "Series metadata: source_key (FRED series ID), units, frequency (D/W/M/Q/A), date_from, date_to, fields" } }, "description": "Station f(x) response with metadata and pre-computed derived metrics" }, "example": { "data": [ { "date": "2024-01-01", "value": 5.33, "mom_pct": 0, "yoy_change": 0.5, "zscore_12m": 1.2, "trend_direction": 1 } ], "meta": { "frequency": "M", "source_key": "PAYEMS" } } } ``` ## More - Live health (JSON, refreshed every minute): https://www.zero.xyz/c/stationfx-total-nonfarm-payrolls-339d258d/health.json - [Zero catalog index](https://www.zero.xyz/llms.txt) - [Other services from stationfx.com](https://www.zero.xyz/host/stationfx.com/llms.txt)