query_ai_infrastructure_construction_v1

shallow

build.exascale/osint · Verify this server

Query verified U.S. private construction spending ($ millions) for data centers and semiconductor/computer-electronics manufacturing plants, from the U.S. Census Bureau's Value of Construction Put in Place (C30). Use this for "how much is being spent BUILDING data centers (or chip fabs) in the US" questions — the construction buildout in dollars, not capacity or investment. Filter by `category` ("data_center" — Census's named subcategory under Office; or "computer_electronic_electrical" — the semiconductor/computer-electronics manufacturing line under Manufacturing), `basis` ("seasonally_adjusted" = a seasonally-adjusted ANNUAL RATE, or "not_seasonally_adjusted" = the NOT-adjusted MONTHLY LEVEL), `data_month` (one month, ISO first-of-month e.g. "2026-04-01") or the `data_month_from`/`data_month_to` range, `year`, and `revision_status` ("preliminary", "revised", or "final"). Group by any of `category`, `basis`, `data_month`, `year`, or `revision_status`. Pass each parameter as a top-level key of `params` (flat — not nested under a `filter`, `filters`, or `where` key). Example: `{"category": "data_center", "basis": "seasonally_adjusted", "data_month": "2026-04-01"}` for one month; add `"group_by": ["data_month"]` over a `data_month_from`/`data_month_to` range for a series. Returns JSON aggregates with citations and optional row-level records when `include_records` is true — every value cites the exact Census workbook, sheet, row, and column. The two categories are DISTINCT series and are never conflated: `data_center` is data-center buildings; `computer_electronic_electrical` is the chip/electronics-manufacturing (fab) line — the CHIPS-Act build-out. `basis` is the other fork: the seasonally-adjusted series is an ANNUAL RATE (what the current monthly pace annualizes to), while the not-seasonally-adjusted series is the actual MONTHLY LEVEL. `revision_status` carries Census's own preliminary/revised/final marking verbatim. Data is monthly; the data-center series begins 2014-01. The response `as_of` is the release vintage (Census revises monthly); pin `as_of` to an earlier vintage to reproduce what was served then. NOT additive: `construction_spending_musd` is a published per-(category, basis, month) reading, so a total that mixes the two bases (an annual rate + a monthly level), or that sums the seasonally-adjusted ANNUAL-RATE series across months, is not a real figure — such a result carries a `construction_aggregation` scope note and ranking remainders omit the metric. Filter to one `basis` and `group_by data_month` for a series over time. Does not determine total data-center INVESTMENT (servers, chips, cooling, equipment — this is construction put-in-place only; Census does not publish an investment total), data-center MW capacity, count, square footage, or location (use the power.* capabilities for capacity and the interconnection queue), which company or project is building (Census C30 has no operator breakdown), public or government construction (this is PRIVATE construction only), or construction outside these two categories.

100.0/100

1 trials · measured 8 days ago

query_ai_infrastructure_construction_v1 scores 100.0/100 on Vouch's measured behaviour index, from 1 real invocation trials against build.exascale/osint, measured 25 Aug 2026 under methodology v0.2.0. Every measured component scored 100.

Component breakdown

ComponentWeightValue
Reliability35%not applicable
Schema integrity25%100.0
Failure behaviour15%not applicable
Latency15%not applicable
Concurrency10%not applicable

Tool details

Transport
remote
Credential class
open
Input schema
not declared
Output schema
not declared
Side-effect classification
unclassified

Score history

DayScoreTierMethodology
2026-08-25100.0shallowv0.2.0

Probe evidence

ProbeOutcomes
schema_integritypass: 1

Raw request/response logs are not archived yet — the outcome counts above are drawn directly from every recorded trial.

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Vouch score: query_ai_infrastructure_construction_v1
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