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 88 5.0085 9371 938.64 8432.36 898.3593 5.3335 10.6664 0.5342 4 United Kingdom 451 451 9 1.9956 3299 489.10 2809.90 574.5042 7.3149 54.3444 1.0845 1 Canada 316 316 10 3.1646 1029 374.30 654.70 174.9132 3.2563 37.43 1.1845 3 Australia 292 292 13 4.4521 1650 119.23 1530.77 1283.8799 5.6507 9.1715 0.4083 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": 0.534228799, "conv_rate": 5.0085, "cpa": 10.666363636, "epc": 5.33352305, "id": 2, "name": "United States", "roi": 898.35932839, "total_click_throughs": 1757, "total_clicks": 1757, "total_cost": 938.64, "total_income": 9371, "total_leads": 88, "total_net": 8432.36 }, { "avg_cpc": 1.084478935, "conv_rate": 1.9956, "cpa": 54.344444444, "epc": 7.314855875, "id": 4, "name": "United Kingdom", "roi": 574.504191372, "total_click_throughs": 451, "total_clicks": 451, "total_cost": 489.1, "total_income": 3299, "total_leads": 9, "total_net": 2809.9 }, { "avg_cpc": 1.18449367, "conv_rate": 3.1646, "cpa": 37.43, "epc": 3.256329113, "id": 1, "name": "Canada", "roi": 174.913171253, "total_click_throughs": 316, "total_clicks": 316, "total_cost": 374.3, "total_income": 1029, "total_leads": 10, "total_net": 654.7 }, { "avg_cpc": 0.408321917, "conv_rate": 4.4521, "cpa": 9.171538461, "epc": 5.650684931, "id": 3, "name": "Australia", "roi": 1283.879895999, "total_click_throughs": 292, "total_clicks": 292, "total_cost": 119.23, "total_income": 1650, "total_leads": 13, "total_net": 1530.77 }, { "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 2026-10-07 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 315 472 157 49.84 4.1968 31.586 652.62 10 15 50 1242 2290 84.38 2 Coffee Subscription / US 241 304 63 26.14 3.2109 20.3435 533.58 11 15 36.36 482 506 4.98 4 Project Tool Pro Annual / US 125 183 58 46.40 1.6654 12.2463 635.33 8 5 -37.50 3024 2220 -26.59 5 Free Trial to Paid / CA 121 177 56 46.28 1.6121 11.8447 634.73 6 9 50 174 261 50 6 Bakery Pre-orders / Local 98 139 41 41.84 1.3057 9.3018 612.41 8 15 87.50 594 999 68.18 3 Standing Desk Launch / UK 205 233 28 13.66 2.7313 15.5922 470.88 2 3 50 1213 694 -42.79 7 Holiday Gift Cards / AU 130 157 27 20.77 1.732 10.5064 506.59 5 8 60 500 1150 130 Split at 2026-10-07T00:00:00Z (1791331200); window: default --days 90 before 2026-07-23T22:38:23Z .. 2026-10-06T23:59:59Z 75.06 days clicks 1235 (16.45/day) conversions 50 (0.67/day) revenue 7229 (96.31/day) after 2026-10-07T00:00:00Z .. 2026-10-21T22:38:23Z 14.94 days clicks 1665 (111.42/day) conversions 70 (4.68/day) revenue 8120 (543.39/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 2026-10-07 --json { "data": [ { "clicks_after": 472, "clicks_before": 315, "clicks_change": 157, "clicks_change_pct": 49.84, "clicks_per_day_after": 31.586, "clicks_per_day_before": 4.1968, "clicks_per_day_change": 27.3892, "clicks_per_day_change_pct": 652.62, "conversions_after": 15, "conversions_before": 10, "conversions_change": 5, "conversions_change_pct": 50, "conversions_per_day_after": 1.0038, "conversions_per_day_before": 0.1332, "conversions_per_day_change": 0.8706, "conversions_per_day_change_pct": 653.41, "id": 1, "name": "Spring Collection / US", "revenue_after": 2290, "revenue_before": 1242, "revenue_change": 1048, "revenue_change_pct": 84.38, "revenue_per_day_after": 153.2456, "revenue_per_day_before": 16.5475, "revenue_per_day_change": 136.6981, "revenue_per_day_change_pct": 826.1 }, { "clicks_after": 304, "clicks_before": 241, "clicks_change": 63, "clicks_change_pct": 26.14, "clicks_per_day_after": 20.3435, "clicks_per_day_before": 3.2109, "clicks_per_day_change": 17.1326, "clicks_per_day_change_pct": 533.58, "conversions_after": 15, "conversions_before": 11, "conversions_change": 4, "conversions_change_pct": 36.36, "conversions_per_day_after": 1.0038, "conversions_per_day_before": 0.1466, "conversions_per_day_change": 0.8572, "conversions_per_day_change_pct": 584.92, "id": 2, "name": "Coffee Subscription / US", "revenue_after": 506, "revenue_before": 482, "revenue_change": 24, "revenue_change_pct": 4.98, "revenue_per_day_after": 33.8613, "revenue_per_day_before": 6.4218, "revenue_per_day_change": 27.4394, "revenue_per_day_change_pct": 427.28 }, { "clicks_after": 183, "clicks_before": 125, "clicks_change": 58, "clicks_change_pct": 46.4, "clicks_per_day_after": 12.2463, "clicks_per_day_before": 1.6654, "clicks_per_day_change": 10.5809, "clicks_per_day_change_pct": 635.33, "conversions_after": 5, "conversions_before": 8, "conversions_change": -3, "conversions_change_pct": -37.5, "conversions_per_day_after": 0.3346, "conversions_per_day_before": 0.1066, "conversions_per_day_change": 0.228, "conversions_per_day_change_pct": 213.92, "id": 4, "name": "Project Tool Pro Annual / US", "revenue_after": 2220, "revenue_before": 3024, "revenue_change": -804, "revenue_change_pct": -26.59, "revenue_per_day_after": 148.5612, "revenue_per_day_before": 40.2896, "revenue_per_day_change": 108.2717, "revenue_per_day_change_pct": 268.73 }, { "clicks_after": 177, "clicks_before": 121, "clicks_change": 56, "clicks_change_pct": 46.28, "clicks_per_day_after": 11.8447, "clicks_per_day_before": 1.6121, "clicks_per_day_change": 10.2326, "clicks_per_day_change_pct": 634.73, "conversions_after": 9, "conversions_before": 6, "conversions_change": 3, "conversions_change_pct": 50, "conversions_per_day_after": 0.6023, "conversions_per_day_before": 0.0799, "conversions_per_day_change": 0.5223, "conversions_per_day_change_pct": 653.41, "id": 5, "name": "Free Trial to Paid / CA", "revenue_after": 261, "revenue_before": 174, "revenue_change": 87, "revenue_change_pct": 50, "revenue_per_day_after": 17.466, "revenue_per_day_before": 2.3182, "revenue_per_day_change": 15.1477, "revenue_per_day_change_pct": 653.41 }, { "clicks_after": 139, "clicks_before": 98, "clicks_change": 41, "clicks_change_pct": 41.84, "clicks_per_day_after": 9.3018, "clicks_per_day_before": 1.3057, "clicks_per_day_change": 7.9961, "clicks_per_day_change_pct": 612.41, "conversions_after": 15, "conversions_before": 8, "conversions_change": 7, "conversions_change_pct": 87.5, "conversions_per_day_after": 1.0038, "conversions_per_day_before": 0.1066, "conversions_per_day_change": 0.8972, "conversions_per_day_change_pct": 841.77, "id": 6, "name": "Bakery Pre-orders / Local", "revenue_after": 999, "revenue_before": 594, "revenue_change": 405, "revenue_change_pct": 68.18, "revenue_per_day_after": 66.8526, "revenue_per_day_before": 7.914, "revenue_per_day_change": 58.9385, "revenue_per_day_change_pct": 744.74 }, { "clicks_after": 233, "clicks_before": 205, "clicks_change": 28, "clicks_change_pct": 13.66, "clicks_per_day_after": 15.5922, "clicks_per_day_before": 2.7313, "clicks_per_day_change": 12.861, "clicks_per_day_change_pct": 470.88, "conversions_after": 3, "conversions_before": 2, "conversions_change": 1, "conversions_change_pct": 50, "conversions_per_day_after": 0.2008, "conversions_per_day_before": 0.0266, "conversions_per_day_change": 0.1741, "conversions_per_day_change_pct": 653.41, "id": 3, "name": "Standing Desk Launch / UK", "revenue_after": 694, "revenue_before": 1213, "revenue_change": -519, "revenue_change_pct": -42.79, "revenue_per_day_after": 46.4421, "revenue_per_day_before": 16.1611, "revenue_per_day_change": 30.281, "revenue_per_day_change_pct": 187.37 }, { "clicks_after": 157, "clicks_before": 130, "clicks_change": 27, "clicks_change_pct": 20.77, "clicks_per_day_after": 10.5064, "clicks_per_day_before": 1.732, "clicks_per_day_change": 8.7743, "clicks_per_day_change_pct": 506.59, "conversions_after": 8, "conversions_before": 5, "conversions_change": 3, "conversions_change_pct": 60, "conversions_per_day_after": 0.5354, "conversions_per_day_before": 0.0666, "conversions_per_day_change": 0.4687, "conversions_per_day_change_pct": 703.64, "id": 7, "name": "Holiday Gift Cards / AU", "revenue_after": 1150, "revenue_before": 500, "revenue_change": 650, "revenue_change_pct": 130, "revenue_per_day_after": 76.9574, "revenue_per_day_before": 6.6616, "revenue_per_day_change": 70.2958, "revenue_per_day_change_pct": 1055.23 } ], "meta": { "after": { "clicks": 1665, "clicks_per_day": 111.4209, "conversions": 70, "conversions_per_day": 4.6844, "days": 14.9433, "revenue": 8120, "revenue_per_day": 543.3861, "rows": 7, "seconds": 1291104, "time_from": 1791331200, "time_from_utc": "2026-10-07T00:00:00Z", "time_to": 1792622303, "time_to_utc": "2026-10-21T22:38:23Z" }, "before": { "clicks": 1235, "clicks_per_day": 16.4542, "conversions": 50, "conversions_per_day": 0.6662, "days": 75.0567, "revenue": 7229, "revenue_per_day": 96.3139, "rows": 7, "seconds": 6484897, "time_from": 1784846303, "time_from_utc": "2026-07-23T22:38:23Z", "time_to": 1791331199, "time_to_utc": "2026-10-06T23:59:59Z" }, "group_by": "campaign", "returned": 7, "rows": 7, "sort": "clicks_change", "sort_by": "absolute value", "sort_dir": "DESC", "split_at": 1791331200, "split_at_utc": "2026-10-07T00:00:00Z", "window": { "source": "default --days 90", "time_from": 1784846303, "time_to": 1792622303 } } }
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, 6 no Pro licence on the install.
{
"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
}
]
}