# StationFX Advance Retail Sales (Retail Trade & Food Services) > StationFX Advance Retail Sales (Retail Trade & Food Services) is a paid API for AI agents from stationfx.com, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-29). Returns monthly U.S. advance retail sales data covering retail trade and food services, with derived statistics for GDP nowcasting and consumer health assessment. ## Facts - Endpoint: GET https://stationfx.com/economic-data/sentiment/advance-retail-sales-retail-trade-and-food-services?utm_source=zero.xyz - Price: $0.005/call - Payment: x402 - Status: unknown - Last checked: 2026-09-29 - Activations on Zero: 0 - Tags: x402 - Canonical page: https://www.zero.xyz/c/stationfx-advance-retail-sales-retail-trade-food-services-a0a60316 - Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_KB70CMMIk5-iSGD9Lz2_D 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-advance-retail-sales-retail-trade-food-services-a0a60316 ``` Example prompt: Pull the StationFX advance retail sales series for the last 6 months — I want the month-over-month percent change, year-over-year percent change, and 5-year z-score for each observation, in JSON format. ## When to prefer this Choose this endpoint when you need a timely, early read on U.S. consumer spending — particularly for GDP nowcasting since advance retail sales is released early in the following month before most other hard economic data. Prefer it over sentiment surveys when you need actual transaction-based spending data. The pre-computed MoM/YoY changes, z-scores, and trend indicators save downstream computation versus raw Census Bureau feeds. The micro-cost per call ($0.005 USDC) makes it suitable for frequent polling in monitoring or alerting workflows. ## Known failure modes - Invalid date format returns an error — dates must be YYYY-MM-DD - Requesting field names not in the available metrics set may return empty or error - Date range with no available data (future dates or pre-series dates) returns empty data array - Invalid fmt enum value (not 'json' or 'toon') may cause a parse error - Missing required 'input' object in request body returns validation error ## How this service works Monthly measure of consumer spending at retail outlets and food service establishments. Covers about 30% of personal consumption. Released early in the following month, one of the first hard data points for current-quarter GDP. Use for consumer health assessment and GDP nowcasting. ## Output Returns a JSON array of monthly observations, each containing the observation date, raw value in series units, month-over-month and year-over-year absolute and percentage changes, 12-month and 5-year z-scores, 5-year percentile rank, 3-month and 12-month rolling averages, and a binary above-trend indicator. The compact 'toon' format is available for token-efficient agent consumption. ## Request schema (JSON Schema) ```json { "type": "object", "$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": "RSAFS" } } } ``` ## More - Live health (JSON, refreshed every minute): https://www.zero.xyz/c/stationfx-advance-retail-sales-retail-trade-food-services-a0a60316/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)