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).

tests/testthat/test-revenue.R

@@ -0,0 +1,38 @@
+test_that("cog_revenue returns expected shape for Broward Property Tax 2020", {
+  skip_if_no_corpus()
+  r <- cog_revenue("101006006", years = 2020L, category = "Property Tax")
+  expect_s3_class(r, "tbl_df")
+  expected_cols <- c("year", "canonical_govid", "gov_name", "revenue_subtype",
+                     "category", "amt_nominal", "codes_included",
+                     "aggregate_fallback", "notes")
+  expect_true(all(expected_cols %in% names(r)))
+  expect_equal(unique(r$canonical_govid), "101006006")
+  expect_equal(unique(r$year), 2020L)
+})
+
+test_that("cog_revenue with no category filter returns multiple categories", {
+  skip_if_no_corpus()
+  r <- cog_revenue("101006006", years = 2020L)
+  expect_gt(length(unique(r$category)), 1L)
+})
+
+test_that("cog_revenue with per_capita + adjust_to_year adds all columns", {
+  skip_if_no_corpus()
+  r <- cog_revenue("101006006", 2020L,
+                   per_capita = TRUE, adjust_to_year = 2022L)
+  expect_true(all(c("amt_nominal", "amt_real",
+                    "amt_per_capita_nominal", "amt_per_capita_real") %in%
+                  names(r)))
+})
+
+test_that("cog_revenue result has provenance attribute", {
+  skip_if_no_corpus()
+  r <- cog_revenue("101006006", 2020L)
+  prov <- attr(r, "provenance")
+  expect_equal(prov$verb, "cog_revenue")
+  expect_true(grepl("revenue_annotated", prov$sql_query))
+})
+
+test_that("cog_revenue rejects invalid inputs", {
+  expect_error(cog_revenue(123, 2020L), "character")
+})