get_station_status¶

Science¶

Negative evidence starts with a fact about the archive, not about the event: did this station have data in the window? The tool reads a precomputed daily availability table (never a live scan of the archive) and classifies each requested station — defaulting to the QC list — as one of three frozen states.

State	Rule	Evidential weight
`delivering`	Coverage ≥ 90 % of the window	If there is no pick, the station was genuinely recording. That silence can be evidence
`silent`	Coverage < 90 %, but data exist within ± 7 days	A telemetry or archive gap. No weight as “the earth was quiet”
`absent`	No data within ± 7 days of the window	Not installed or not archived. Must never be counted as quiet

An optional origin_ref adds epicentral distance and azimuth so the same rows can be read as a geometry. Warnings fire for explicitly requested stations that are absent or silent, and availability_stale when the table has no row for the requested UTC day — zero delivering may then mean a missing day, not a quiet network.

Delivering is not the same as detectable. Noise and distance are predict_detectability and explain_silence.

Contract¶

Generated from the live registry (ToolSpec). Field names, types and defaults come from the input and payload models; they are not hand-typed.


Group	`inventory`
Class	2
Tool version	`1.1.0`
Highest declared tier	F
Timeout	5 s
Budget key	`none`
`readOnlyHint`	true
`idempotentHint`	true

Input¶

Field	Type	Required	Notes
`t_from_utc`	string	yes
`t_to_utc`	string	yes
`stations`	array[string] \| null	no	default `null`
`origin_ref`	object (kind `catalog` \| `solution` \| `value`) \| null	no	default `null`

Payload¶

Field	Type	Required	Notes
`window`	object	yes
`window.from_utc`	string	yes
`window.to_utc`	string	yes
`stations`	array[object]	yes
`stations[].station_id`	string	yes
`stations[].state`	string ∈ {`delivering`, `silent`, `absent`}	yes
`stations[].coverage_pct`	number	yes
`stations[].gaps`	array[object]	yes
`stations[].gaps[].from_utc`	string	yes
`stations[].gaps[].to_utc`	string	yes
`stations[].sample_rate_hz`	number \| null	no	default `null`
`stations[].distance_km`	number \| null	no	default `null`
`stations[].azimuth_deg`	number \| null	no	default `null`
`counts`	object	yes
`counts.delivering`	integer	yes
`counts.silent`	integer	yes
`counts.absent`	integer	yes
`table_version`	string	yes

Example request¶

{
  "t_from_utc": "2024-06-15T08:00:00.000Z",
  "t_to_utc": "2024-06-15T09:00:00.000Z",
  "stations": [
    "XX.STA1"
  ],
  "origin_ref": {
    "kind": "catalog",
    "event_id": 1001
  }
}

Example payload¶

{
  "window": {
    "from_utc": "2024-06-15T08:00:00.000Z",
    "to_utc": "2024-06-15T09:00:00.000Z"
  },
  "stations": [
    {
      "station_id": "XX.STA1",
      "state": "delivering",
      "coverage_pct": 100.0,
      "gaps": [],
      "sample_rate_hz": 100.0,
      "distance_km": 41.2,
      "azimuth_deg": 212.0
    }
  ],
  "counts": {
    "delivering": 26,
    "silent": 2,
    "absent": 4
  },
  "table_version": "2024-06-01"
}

What this tool does not tell you¶

What this tool does not tell you: whether a delivering station could have detected anything — that depends on noise and distance (predict_detectability, explain_silence).

Warnings named for this tool¶

Code	When
`station_absent`	an explicitly requested station is absent
`station_silent`	an explicitly requested station is silent
`availability_stale`	the availability table has no row for the requested UTC day