feat: cog_spending + cog_revenue + cog_explain

Three core query verbs over the spending_annotated / revenue_annotated
DuckDB views. Each verb accepts vector govid, vector years, optional
category filter, per_capita flag, and adjust_to_year for CPI-U
real-dollar conversion (bundled index).

Amounts are returned in full USD (SUM(amt) * 1000) so callers can
freely rescale to millions/billions. The $1,000s -> $USD conversion
is recorded in provenance$transformations$units_conversion.

Every result carries an attr(., "provenance") list matching
inst/schemas/provenance-v1.json. cog_explain() prints the structured
form via cli or returns the raw list for MCP/JSON consumers.

Also: .fetch_or_cache_manifest() now handles local fixture paths so
tests can point USCOGDATA_FIXTURE_URL at the pipeline publish_cache/
without a working HTTP server.

Tests: 80 pass / 0 fail. devtools::check() 0E/0W/2N (both notes
pre-existing / environmental).

R/revenue.R

@@ -0,0 +1,29 @@
+# R/revenue.R
+
+#' Summarized revenue by category
+#'
+#' Mirror of [cog_spending()] for revenue categories. One row per
+#' `(year, canonical_govid, revenue_subtype, category)`. Amounts are returned
+#' in **full U.S. dollars** (raw Census values are in $1,000s; this verb
+#' multiplies by 1000 and records the conversion in `provenance`).
+#'
+#' @inheritParams cog_spending
+#' @return Tibble with columns `year`, `canonical_govid`, `gov_name`,
+#'   `revenue_subtype`, `category`, `amt_nominal`, optional `amt_real`,
+#'   optional `amt_per_capita_nominal`, optional `amt_per_capita_real`,
+#'   `codes_included`, `aggregate_fallback`, `notes`.
+#' @export
+cog_revenue <- function(govid, years, category = NULL,
+                        per_capita = FALSE, adjust_to_year = NULL) {
+  .verb_spendrev(
+    verb           = "cog_revenue",
+    view           = "revenue_annotated",
+    subtype_col    = "revenue_subtype",
+    call           = match.call(),
+    govid          = govid,
+    years          = years,
+    category       = category,
+    per_capita     = per_capita,
+    adjust_to_year = adjust_to_year
+  )
+}