01Run it
Replace the <placeholders> with your own values, or use the builder below.
p202 attribution journey <conv_id>02What 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 attribution journey 31 amount: 63.00000 click_id: 760 conv_id: 31 conv_time: 1792069812 counted: true credits: [{"model_id":1,"model_name":"Last touch","model_type":"last_touch","touches":[{"click_id":760,"credit":"1.00000000","position":0,"revenue":"63.00000"}]},{"model_id":2,"model_name":"First touch","model_type":"first_touch","touches":[{"click_id":760,"credit":"1.00000000","position":0,"revenue":"63.00000"}]},{"model_id":3,"model_name":"Position based (40/20/40)","model_type":"position_based","touches":[{"click_id":760,"credit":"1.00000000","position":0,"revenue":"63.00000"}]}] journey: {"built_at":1792622059,"built_lookback_days":30,"identified":true,"touches":1,"truncated":false} pending: recorded_amount: 63.00000 touches: [{"campaign_id":6,"campaign_name":"Bakery Pre-orders / Local","click_id":760,"click_time":1792067092,"position":0,"ppc_account_id":3,"ppc_account_name":"Social Ads - Prospecting","signals":["cust","vid"]}]
$ p202 attribution journey 31 --json { "data": { "amount": "63.00000", "click_id": 760, "conv_id": 31, "conv_time": 1792069812, "counted": true, "credits": [ { "model_id": 1, "model_name": "Last touch", "model_type": "last_touch", "touches": [ { "click_id": 760, "credit": "1.00000000", "position": 0, "revenue": "63.00000" } ] }, { "model_id": 2, "model_name": "First touch", "model_type": "first_touch", "touches": [ { "click_id": 760, "credit": "1.00000000", "position": 0, "revenue": "63.00000" } ] }, { "model_id": 3, "model_name": "Position based (40/20/40)", "model_type": "position_based", "touches": [ { "click_id": 760, "credit": "1.00000000", "position": 0, "revenue": "63.00000" } ] } ], "journey": { "built_at": 1792622059, "built_lookback_days": 30, "identified": true, "touches": 1, "truncated": false }, "pending": null, "recorded_amount": "63.00000", "touches": [ { "campaign_id": 6, "campaign_name": "Bakery Pre-orders / Local", "click_id": 760, "click_time": 1792067092, "position": 0, "ppc_account_id": 3, "ppc_account_name": "Social Ads - Prospecting", "signals": [ "cust", "vid" ] } ] } }
03Build your command
Pick values and the command line writes itself, quoted and ready to paste.
p202 attribution journeySet flags below; the command updates as you type.
04For agents
Running this from an agent
- Read the same facts as JSON:
p202 commands attribution journey --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 attribution journey",
"use": "journey <conv_id>",
"short": "One conversion's journey: its touches, the identity signals that linked them, and every model's credit",
"runnable": true
}