01Run it
Replace the <placeholders> with your own values, or use the builder below.
p202 attribution model list02What 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 list status created_at is_default lookback_days model_id model_name model_slug model_type recompute_pending status_reason updated_at weighting_config ------ ---------- ---------- ------------- -------- ------------------------- ----------------------- -------------- ----------------- ------------- ---------- -------------------------------------- active 1791538968 true 30 1 Last touch last-touch last_touch false 1791538968 {} active 1791539625 false 30 2 First touch first-touch first_touch false 1791539625 {} active 1791539626 false 30 3 Position based (40/20/40) position-based-40-20-40 position_based false 1791539626 {"first_weight":0.4,"last_weight":0.4}
$ p202 attribution model list --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": {} }, { "created_at": 1791539625, "is_default": false, "lookback_days": 30, "model_id": 2, "model_name": "First touch", "model_slug": "first-touch", "model_type": "first_touch", "recompute_pending": false, "status": "active", "status_reason": null, "updated_at": 1791539625, "weighting_config": {} }, { "created_at": 1791539626, "is_default": false, "lookback_days": 30, "model_id": 3, "model_name": "Position based (40/20/40)", "model_slug": "position-based-40-20-40", "model_type": "position_based", "recompute_pending": false, "status": "active", "status_reason": null, "updated_at": 1791539626, "weighting_config": { "first_weight": 0.4, "last_weight": 0.4 } } ] }
03Build your command
Pick values and the command line writes itself, quoted and ready to paste.
p202 attribution model listSet flags below; the command updates as you type.
04Flags
1 flag, plus the global flags every command takes.
| Flag | What it does |
|---|---|
| --type, -tstring | Filter by type: last_touch, first_touch, linear, time_decay, position_basedlast_touchfirst_touchlineartime_decayposition_based |
05For agents
Running this from an agent
- Read the same facts as JSON:
p202 commands attribution model list --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 list",
"use": "list",
"short": "List attribution models",
"runnable": true,
"flags": [
{
"name": "type",
"shorthand": "t",
"type": "string",
"default": "",
"usage": "Filter by type: last_touch, first_touch, linear, time_decay, position_based",
"allowed_values": [
"last_touch",
"first_touch",
"linear",
"time_decay",
"position_based"
],
"required": false
}
]
}