01Run it
Replace the <placeholders> with your own values, or use the builder below.
p202 attribution model get <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 model get 1 created_at: 1791538968 is_default: true lookback_days: 30 model_id: 1 model_name: Last touch model_slug: last-touch model_type: last_touch recompute_pending: false status: active status_reason: updated_at: 1791538968 weighting_config: {}
$ p202 attribution model get 1 --json { "data": { "created_at": 1791538968, "is_default": true, "lookback_days": 30, "model_id": 1, "model_name": "Last touch", "model_slug": "last-touch", "model_type": "last_touch", "recompute_pending": false, "status": "active", "status_reason": null, "updated_at": 1791538968, "weighting_config": {} } }
03Build your command
Pick values and the command line writes itself, quoted and ready to paste.
p202 attribution model getSet flags below; the command updates as you type.
04For agents
Running this from an agent
- Read the same facts as JSON:
p202 commands attribution model get --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 attribution model get",
"use": "get <id>",
"short": "Get an attribution model",
"runnable": true
}