01Run it
Straight from the command's own help.
p202 analytics --group-by country --period last30p202 analytics --group-by country --split-at 2026-09-0402What you get
Captured from the real binary, run against a demo store with 30 days of traffic. Switch tabs to see the same run as JSON, the shape scripts and agents parse.
$ p202 analytics --group-by country --period last30 id name Clicks Clickthroughs Conversions Conv % Revenue Cost Profit ROI % EPC CPA Avg CPC -- -------------- ------ ------------- ----------- ------ ------- ------ ------- -------- ------ ------- ------- 2 United States 1757 1757 79 4.4963 8321 938.44 7382.56 786.6843 4.7359 11.879 0.5341 3 United Kingdom 451 451 10 2.2173 4487 489.10 3997.90 817.3993 9.949 48.91 1.0845 1 Canada 316 316 18 5.6962 1231 374.30 856.70 228.8806 3.8956 20.7944 1.1845 4 Australia 293 293 14 4.7782 1798 119.54 1678.46 1404.099 6.1365 8.5386 0.408 5 Germany 84 84 0 0 0 111.60 -111.60 -100 0 0 1.3286
$ p202 analytics --group-by country --period last30 --json { "available_breakdowns": [ "campaign", "aff_network", "ppc_account", "ppc_network", "landing_page", "keyword", "country", "city", "region", "browser", "platform", "device", "isp", "text_ad", "ip", "referer", "referer_url", "device_type", "c1", "c2", "c3", "c4", "utm_source", "utm_medium", "utm_campaign", "utm_term", "utm_content", "rotator", "rotator_rule" ], "breakdown": "country", "data": [ { "avg_cpc": 0.534114968, "conv_rate": 4.4963, "cpa": 11.878987341, "epc": 4.735913488, "id": 2, "name": "United States", "roi": 786.684284557, "total_click_throughs": 1757, "total_clicks": 1757, "total_cost": 938.44, "total_income": 8321, "total_leads": 79, "total_net": 7382.56 }, { "avg_cpc": 1.084478935, "conv_rate": 2.2173, "cpa": 48.91, "epc": 9.949002217, "id": 3, "name": "United Kingdom", "roi": 817.399304846, "total_click_throughs": 451, "total_clicks": 451, "total_cost": 489.1, "total_income": 4487, "total_leads": 10, "total_net": 3997.9 }, { "avg_cpc": 1.18449367, "conv_rate": 5.6962, "cpa": 20.794444444, "epc": 3.89556962, "id": 1, "name": "Canada", "roi": 228.880577077, "total_click_throughs": 316, "total_clicks": 316, "total_cost": 374.3, "total_income": 1231, "total_leads": 18, "total_net": 856.7 }, { "avg_cpc": 0.407986348, "conv_rate": 4.7782, "cpa": 8.538571428, "epc": 6.136518771, "id": 4, "name": "Australia", "roi": 1404.099046344, "total_click_throughs": 293, "total_clicks": 293, "total_cost": 119.54, "total_income": 1798, "total_leads": 14, "total_net": 1678.46 }, { "avg_cpc": 1.328571428, "conv_rate": 0, "cpa": 0, "epc": 0, "id": 5, "name": "Germany", "roi": -100, "total_click_throughs": 84, "total_clicks": 84, "total_cost": 111.6, "total_income": 0, "total_leads": 0, "total_net": -111.6 } ] }
Profit by country
Drawn from the JSON output above. Losses run left of zero in orange.
$ p202 analytics --group-by campaign --split-at 2026-09-25 id name clicks_before clicks_after clicks_change clicks_change_pct clicks_per_day_before clicks_per_day_after clicks_per_day_change_pct conversions_before conversions_after conversions_change_pct revenue_before revenue_after revenue_change_pct -- ---------------------------- ------------- ------------ ------------- ----------------- --------------------- -------------------- ------------------------- ------------------ ----------------- ---------------------- -------------- ------------- ------------------ 1 Spring Collection / US 340 447 107 31.47 4.4985 31.0009 589.14 13 11 -15.38 1916 1462 -23.70 5 Free Trial to Paid / CA 116 182 66 56.90 1.5348 12.6223 722.42 7 11 57.14 203 319 57.14 6 Bakery Pre-orders / Local 95 143 48 50.53 1.2569 9.9175 689.03 11 7 -36.36 888 492 -44.59 2 Coffee Subscription / US 251 293 42 16.73 3.3209 20.3205 511.89 17 13 -23.53 674 442 -34.42 3 Standing Desk Launch / UK 208 230 22 10.58 2.752 15.9513 479.62 3 5 66.67 1702 1849 8.64 7 Holiday Gift Cards / AU 136 152 16 11.76 1.7994 10.5417 485.85 5 8 60 475 975 105.26 4 Project Tool Pro Annual / US 151 157 6 3.97 1.9979 10.8885 445.01 3 7 133.33 1284 3156 145.79 Split at 2026-09-25T00:00:00Z (1790294400); window: default --days 90 before 2026-07-11T10:03:14Z .. 2026-09-24T23:59:59Z 75.58 days clicks 1297 (17.16/day) conversions 59 (0.78/day) revenue 7142 (94.49/day) after 2026-09-25T00:00:00Z .. 2026-10-09T10:03:14Z 14.42 days clicks 1604 (111.24/day) conversions 62 (4.3/day) revenue 8695 (603.03/day) 7 value(s), 7 shown, ranked by |clicks_change| DESC. The sides differ in length: compare the *_per_day columns, not the totals.
$ p202 analytics --group-by campaign --split-at 2026-09-25 --json { "data": [ { "clicks_after": 447, "clicks_before": 340, "clicks_change": 107, "clicks_change_pct": 31.47, "clicks_per_day_after": 31.0009, "clicks_per_day_before": 4.4985, "clicks_per_day_change": 26.5024, "clicks_per_day_change_pct": 589.14, "conversions_after": 11, "conversions_before": 13, "conversions_change": -2, "conversions_change_pct": -15.38, "conversions_per_day_after": 0.7629, "conversions_per_day_before": 0.172, "conversions_per_day_change": 0.5909, "conversions_per_day_change_pct": 343.54, "id": 1, "name": "Spring Collection / US", "revenue_after": 1462, "revenue_before": 1916, "revenue_change": -454, "revenue_change_pct": -23.7, "revenue_per_day_after": 101.3945, "revenue_per_day_before": 25.3503, "revenue_per_day_change": 76.0443, "revenue_per_day_change_pct": 299.97 }, { "clicks_after": 182, "clicks_before": 116, "clicks_change": 66, "clicks_change_pct": 56.9, "clicks_per_day_after": 12.6223, "clicks_per_day_before": 1.5348, "clicks_per_day_change": 11.0875, "clicks_per_day_change_pct": 722.42, "conversions_after": 11, "conversions_before": 7, "conversions_change": 4, "conversions_change_pct": 57.14, "conversions_per_day_after": 0.7629, "conversions_per_day_before": 0.0926, "conversions_per_day_change": 0.6703, "conversions_per_day_change_pct": 723.71, "id": 5, "name": "Free Trial to Paid / CA", "revenue_after": 319, "revenue_before": 203, "revenue_change": 116, "revenue_change_pct": 57.14, "revenue_per_day_after": 22.1237, "revenue_per_day_before": 2.6859, "revenue_per_day_change": 19.4378, "revenue_per_day_change_pct": 723.71 }, { "clicks_after": 143, "clicks_before": 95, "clicks_change": 48, "clicks_change_pct": 50.53, "clicks_per_day_after": 9.9175, "clicks_per_day_before": 1.2569, "clicks_per_day_change": 8.6606, "clicks_per_day_change_pct": 689.03, "conversions_after": 7, "conversions_before": 11, "conversions_change": -4, "conversions_change_pct": -36.36, "conversions_per_day_after": 0.4855, "conversions_per_day_before": 0.1455, "conversions_per_day_change": 0.3399, "conversions_per_day_change_pct": 233.57, "id": 6, "name": "Bakery Pre-orders / Local", "revenue_after": 492, "revenue_before": 888, "revenue_change": -396, "revenue_change_pct": -44.59, "revenue_per_day_after": 34.1218, "revenue_per_day_before": 11.749, "revenue_per_day_change": 22.3729, "revenue_per_day_change_pct": 190.42 }, { "clicks_after": 293, "clicks_before": 251, "clicks_change": 42, "clicks_change_pct": 16.73, "clicks_per_day_after": 20.3205, "clicks_per_day_before": 3.3209, "clicks_per_day_change": 16.9996, "clicks_per_day_change_pct": 511.89, "conversions_after": 13, "conversions_before": 17, "conversions_change": -4, "conversions_change_pct": -23.53, "conversions_per_day_after": 0.9016, "conversions_per_day_before": 0.2249, "conversions_per_day_change": 0.6767, "conversions_per_day_change_pct": 300.84, "id": 2, "name": "Coffee Subscription / US", "revenue_after": 442, "revenue_before": 674, "revenue_change": -232, "revenue_change_pct": -34.42, "revenue_per_day_after": 30.6542, "revenue_per_day_before": 8.9176, "revenue_per_day_change": 21.7366, "revenue_per_day_change_pct": 243.75 }, { "clicks_after": 230, "clicks_before": 208, "clicks_change": 22, "clicks_change_pct": 10.58, "clicks_per_day_after": 15.9513, "clicks_per_day_before": 2.752, "clicks_per_day_change": 13.1992, "clicks_per_day_change_pct": 479.62, "conversions_after": 5, "conversions_before": 3, "conversions_change": 2, "conversions_change_pct": 66.67, "conversions_per_day_after": 0.3468, "conversions_per_day_before": 0.0397, "conversions_per_day_change": 0.3071, "conversions_per_day_change_pct": 773.63, "id": 3, "name": "Standing Desk Launch / UK", "revenue_after": 1849, "revenue_before": 1702, "revenue_change": 147, "revenue_change_pct": 8.64, "revenue_per_day_after": 128.2343, "revenue_per_day_before": 22.5189, "revenue_per_day_change": 105.7154, "revenue_per_day_change_pct": 469.45 }, { "clicks_after": 152, "clicks_before": 136, "clicks_change": 16, "clicks_change_pct": 11.76, "clicks_per_day_after": 10.5417, "clicks_per_day_before": 1.7994, "clicks_per_day_change": 8.7423, "clicks_per_day_change_pct": 485.85, "conversions_after": 8, "conversions_before": 5, "conversions_change": 3, "conversions_change_pct": 60, "conversions_per_day_after": 0.5548, "conversions_per_day_before": 0.0662, "conversions_per_day_change": 0.4887, "conversions_per_day_change_pct": 738.69, "id": 7, "name": "Holiday Gift Cards / AU", "revenue_after": 975, "revenue_before": 475, "revenue_change": 500, "revenue_change_pct": 105.26, "revenue_per_day_after": 67.6195, "revenue_per_day_before": 6.2846, "revenue_per_day_change": 61.3348, "revenue_per_day_change_pct": 975.95 }, { "clicks_after": 157, "clicks_before": 151, "clicks_change": 6, "clicks_change_pct": 3.97, "clicks_per_day_after": 10.8885, "clicks_per_day_before": 1.9979, "clicks_per_day_change": 8.8906, "clicks_per_day_change_pct": 445.01, "conversions_after": 7, "conversions_before": 3, "conversions_change": 4, "conversions_change_pct": 133.33, "conversions_per_day_after": 0.4855, "conversions_per_day_before": 0.0397, "conversions_per_day_change": 0.4458, "conversions_per_day_change_pct": 1123.09, "id": 4, "name": "Project Tool Pro Annual / US", "revenue_after": 3156, "revenue_before": 1284, "revenue_change": 1872, "revenue_change_pct": 145.79, "revenue_per_day_after": 218.879, "revenue_per_day_before": 16.9884, "revenue_per_day_change": 201.8907, "revenue_per_day_change_pct": 1188.4 } ], "meta": { "after": { "clicks": 1604, "clicks_per_day": 111.2427, "conversions": 62, "conversions_per_day": 4.2999, "days": 14.4189, "revenue": 8695, "revenue_per_day": 603.027, "rows": 7, "seconds": 1245795, "time_from": 1790294400, "time_from_utc": "2026-09-25T00:00:00Z", "time_to": 1791540194, "time_to_utc": "2026-10-09T10:03:14Z" }, "before": { "clicks": 1297, "clicks_per_day": 17.1604, "conversions": 59, "conversions_per_day": 0.7806, "days": 75.5811, "revenue": 7142, "revenue_per_day": 94.4945, "rows": 7, "seconds": 6530206, "time_from": 1783764194, "time_from_utc": "2026-07-11T10:03:14Z", "time_to": 1790294399, "time_to_utc": "2026-09-24T23:59:59Z" }, "group_by": "campaign", "returned": 7, "rows": 7, "sort": "clicks_change", "sort_by": "absolute value", "sort_dir": "DESC", "split_at": 1790294400, "split_at_utc": "2026-09-25T00:00:00Z", "window": { "source": "default --days 90", "time_from": 1783764194, "time_to": 1791540194 } } }
03Build your command
Pick values and the command line writes itself, quoted and ready to paste.
p202 analyticsSet flags below; the command updates as you type.
04Flags
27 flags, plus the global flags every command takes.
| Flag | What it does |
|---|---|
| --aff-campaign-idstring | Filter by INTERNAL campaign id (from campaign list), not the public id in tracking URLs |
| --aff-network-idstring | Filter by affiliate network ID |
| --browser-idstring | Filter by browser ID (the id of a --breakdown browser row) |
| --country-idstring | Filter by country ID |
| --daysint | Relative window: the last N×24 hours, ending now (ignored when --period is provided; --period lastN counts whole days from a midnight) |
| --device-typestring | Filter by device type ID: 1 Desktop, 2 Mobile, 3 Tablet, 4 Bot (the ids of --breakdown device_type rows) |
| --group-bystring | Breakdown dimension: campaign, aff_network, ppc_account, ppc_network, landing_page, keyword, country, city, region, browser, platform, device, isp, text_ad, ip, referer, referer_url, device_type, c1, c2, c3, c4, utm_source, utm_medium, utm_campaign, utm_term, utm_content, rotator, rotator_rule (aliases: geo=country, lp=landing_page, network=aff_network, offer=campaign, referrer=referer, referrer_url=referer_url, rule=rotator_rule, source=ppc_account)campaignaff_networkppc_accountppc_networklanding_pagekeywordcountrycityregionbrowserplatformdeviceisptext_adiprefererreferer_urldevice_typec1c2c3c4utm_sourceutm_mediumutm_campaignutm_termutm_contentrotatorrotator_rulegeo → countrylp → landing_pagenetwork → aff_networkoffer → campaignreferrer → refererreferrer_url → referer_urlrule → rotator_rulesource → ppc_account |
| --ipstring | Only clicks from this one IP address, IPv4 or IPv6 |
| --isp-idstring | Filter by ISP/carrier ID (the id of a --breakdown isp row) |
| --keywordstring | Only clicks whose keyword contains this text (case-insensitive) |
| --landing-page-idstring | Filter by landing page ID |
| --limit, -lstring | Max results |
| --method-of-promotionstring | Only direct-link clicks or only landing-page clicks: directlink, landingpagedirectlinklandingpage |
| --offset, -ostring | Pagination offset |
| --periodstring | Period: today, yesterday, last7, last14, last30, last90, thismonth, lastmonth, thisyear, lastyear, alltimetodayyesterdaylast7last14last30last90thismonthlastmonththisyearlastyearalltime |
| --platform-idstring | Filter by platform (OS) ID (the id of a --breakdown platform row) |
| --ppc-account-idstring | Filter by PPC account ID |
| --ppc-network-idstring | Filter by PPC network ID, or none for the clicks with no traffic source |
| --refererstring | Only clicks whose referring URL contains this text (case-insensitive) |
| --region-idstring | Filter by region ID (the id of a --breakdown region row) |
| --showstring | Which clicks count (default all): all, real, filtered, filtered_bot, leads; real = not filtered, filtered_bot = filtered as bots, leads = convertedallrealfilteredfiltered_botleads |
| --sortstring | Sort by: total_clicks, total_click_throughs, total_leads, total_income, total_cost, total_net, epc, avg_cpc, conv_rate, roi, cpa, clicks_per_day, conversions_per_day, revenue_per_day (aliases: clicks=total_clicks, conversions=total_leads, cost=total_cost, profit=total_net, revenue=total_income)total_clickstotal_click_throughstotal_leadstotal_incometotal_costtotal_netepcavg_cpcconv_rateroicpaclicks_per_dayconversions_per_dayrevenue_per_dayclicks → total_clicksconversions → total_leadscost → total_costprofit → total_netrevenue → total_income |
| --sort-dirstring | Sort direction: ASC, DESCASCDESC |
| --split-atstring | Compare before/after this moment: YYYY-MM-DD (00:00 UTC) or unix seconds. Splits the window (--days N, or --time-from/--time-to in unix seconds; default --days 90) into [start, split) and [split, end] and returns one row per value: clicks/conversions/revenue before, after, change, change %, and per-day rates. --sort clicks|conversions|revenue[_per_day] ranks by absolute change (default clicks) |
| --text-ad-idstring | Filter by text ad ID |
| --time-fromstring | Start: unix seconds, a date (2026-10-01, from its first second in the account's timezone) or a time with its offset (2026-10-01T09:30:00Z) |
| --time-tostring | End, inclusive: unix seconds, a date (2026-10-01, through its last second in the account's timezone) or a time with its offset |
05How it works
Stats grouped by one dimension: the shorthand for p202 report breakdown.
With --split-at, compare before and after a date: each value's totals on both sides, the change, and the daily rate on each side, so two windows of different lengths compare fairly.
06For agents
Running this from an agent
- Read the same facts as JSON:
p202 commands analytics --json. - With
AI_AGENT,CLAUDECODEor another agent variable set, output is compact JSON and errors arrive on stderr as a JSON envelope with ahint. - Exit codes: 0 ok, 1 bad input, 2 auth, 3 network, 4 server error, 5 partial failure.
{
"path": "p202 analytics",
"use": "analytics",
"short": "Query performance stats grouped by campaign, traffic source, country, etc. (shorthand for report breakdown)",
"long": "Stats grouped by one dimension: the shorthand for `p202 report breakdown`.\n\nWith --split-at, compare before and after a date: each value's totals on both\nsides, the change, and the daily rate on each side, so two windows of different\nlengths compare fairly.",
"runnable": true,
"example": "p202 analytics --group-by country --period last30\n p202 analytics --group-by country --split-at 2026-09-04",
"flags": [
{
"name": "aff-campaign-id",
"type": "string",
"default": "",
"usage": "Filter by INTERNAL campaign id (from `campaign list`), not the public id in tracking URLs",
"required": false
},
{
"name": "aff-network-id",
"type": "string",
"default": "",
"usage": "Filter by affiliate network ID",
"required": false
},
{
"name": "browser-id",
"type": "string",
"default": "",
"usage": "Filter by browser ID (the id of a `--breakdown browser` row)",
"required": false
},
{
"name": "country-id",
"type": "string",
"default": "",
"usage": "Filter by country ID",
"required": false
},
{
"name": "days",
"type": "int",
"default": "0",
"usage": "Relative window: the last N×24 hours, ending now (ignored when --period is provided; --period lastN counts whole days from a midnight)",
"required": false
},
{
"name": "device-type",
"type": "string",
"default": "",
"usage": "Filter by device type ID: 1 Desktop, 2 Mobile, 3 Tablet, 4 Bot (the ids of `--breakdown device_type` rows)",
"required": false
},
{
"name": "group-by",
"type": "string",
"default": "",
"usage": "Breakdown dimension: campaign, aff_network, ppc_account, ppc_network, landing_page, keyword, country, city, region, browser, platform, device, isp, text_ad, ip, referer, referer_url, device_type, c1, c2, c3, c4, utm_source, utm_medium, utm_campaign, utm_term, utm_content, rotator, rotator_rule (aliases: geo=country, lp=landing_page, network=aff_network, offer=campaign, referrer=referer, referrer_url=referer_url, rule=rotator_rule, source=ppc_account)",
"allowed_values": [
"campaign",
"aff_network",
"ppc_account",
"ppc_network",
"landing_page",
"keyword",
"country",
"city",
"region",
"browser",
"platform",
"device",
"isp",
"text_ad",
"ip",
"referer",
"referer_url",
"device_type",
"c1",
"c2",
"c3",
"c4",
"utm_source",
"utm_medium",
"utm_campaign",
"utm_term",
"utm_content",
"rotator",
"rotator_rule"
],
"value_aliases": {
"geo": "country",
"lp": "landing_page",
"network": "aff_network",
"offer": "campaign",
"referrer": "referer",
"referrer_url": "referer_url",
"rule": "rotator_rule",
"source": "ppc_account"
},
"required": false
},
{
"name": "ip",
"type": "string",
"default": "",
"usage": "Only clicks from this one IP address, IPv4 or IPv6",
"required": false
},
{
"name": "isp-id",
"type": "string",
"default": "",
"usage": "Filter by ISP/carrier ID (the id of a `--breakdown isp` row)",
"required": false
},
{
"name": "keyword",
"type": "string",
"default": "",
"usage": "Only clicks whose keyword contains this text (case-insensitive)",
"required": false
},
{
"name": "landing-page-id",
"type": "string",
"default": "",
"usage": "Filter by landing page ID",
"required": false
},
{
"name": "limit",
"shorthand": "l",
"type": "string",
"default": "",
"usage": "Max results",
"required": false
},
{
"name": "method-of-promotion",
"type": "string",
"default": "",
"usage": "Only direct-link clicks or only landing-page clicks: directlink, landingpage",
"allowed_values": [
"directlink",
"landingpage"
],
"required": false
},
{
"name": "offset",
"shorthand": "o",
"type": "string",
"default": "",
"usage": "Pagination offset",
"required": false
},
{
"name": "period",
"type": "string",
"default": "",
"usage": "Period: today, yesterday, last7, last14, last30, last90, thismonth, lastmonth, thisyear, lastyear, alltime",
"allowed_values": [
"today",
"yesterday",
"last7",
"last14",
"last30",
"last90",
"thismonth",
"lastmonth",
"thisyear",
"lastyear",
"alltime"
],
"required": false
},
{
"name": "platform-id",
"type": "string",
"default": "",
"usage": "Filter by platform (OS) ID (the id of a `--breakdown platform` row)",
"required": false
},
{
"name": "ppc-account-id",
"type": "string",
"default": "",
"usage": "Filter by PPC account ID",
"required": false
},
{
"name": "ppc-network-id",
"type": "string",
"default": "",
"usage": "Filter by PPC network ID, or none for the clicks with no traffic source",
"required": false
},
{
"name": "referer",
"type": "string",
"default": "",
"usage": "Only clicks whose referring URL contains this text (case-insensitive)",
"required": false
},
{
"name": "region-id",
"type": "string",
"default": "",
"usage": "Filter by region ID (the id of a `--breakdown region` row)",
"required": false
},
{
"name": "show",
"type": "string",
"default": "",
"usage": "Which clicks count (default all): all, real, filtered, filtered_bot, leads; real = not filtered, filtered_bot = filtered as bots, leads = converted",
"allowed_values": [
"all",
"real",
"filtered",
"filtered_bot",
"leads"
],
"required": false
},
{
"name": "sort",
"type": "string",
"default": "",
"usage": "Sort by: total_clicks, total_click_throughs, total_leads, total_income, total_cost, total_net, epc, avg_cpc, conv_rate, roi, cpa, clicks_per_day, conversions_per_day, revenue_per_day (aliases: clicks=total_clicks, conversions=total_leads, cost=total_cost, profit=total_net, revenue=total_income)",
"allowed_values": [
"total_clicks",
"total_click_throughs",
"total_leads",
"total_income",
"total_cost",
"total_net",
"epc",
"avg_cpc",
"conv_rate",
"roi",
"cpa",
"clicks_per_day",
"conversions_per_day",
"revenue_per_day"
],
"value_aliases": {
"clicks": "total_clicks",
"conversions": "total_leads",
"cost": "total_cost",
"profit": "total_net",
"revenue": "total_income"
},
"required": false
},
{
"name": "sort-dir",
"type": "string",
"default": "",
"usage": "Sort direction: ASC, DESC",
"allowed_values": [
"ASC",
"DESC"
],
"required": false
},
{
"name": "split-at",
"type": "string",
"default": "",
"usage": "Compare before/after this moment: YYYY-MM-DD (00:00 UTC) or unix seconds. Splits the window (--days N, or --time-from/--time-to in unix seconds; default --days 90) into [start, split) and [split, end] and returns one row per value: clicks/conversions/revenue before, after, change, change %, and per-day rates. --sort clicks|conversions|revenue[_per_day] ranks by absolute change (default clicks)",
"required": false
},
{
"name": "text-ad-id",
"type": "string",
"default": "",
"usage": "Filter by text ad ID",
"required": false
},
{
"name": "time-from",
"type": "string",
"default": "",
"usage": "Start: unix seconds, a date (2026-10-01, from its first second in the account's timezone) or a time with its offset (2026-10-01T09:30:00Z)",
"required": false
},
{
"name": "time-to",
"type": "string",
"default": "",
"usage": "End, inclusive: unix seconds, a date (2026-10-01, through its last second in the account's timezone) or a time with its offset",
"required": false
}
]
}