fix: literal name search, units docs, peer-summary semantics (#16, #15, #14)

The three kodor/fix issues, taken over after a day with no branch, PR or
comment on any of them. Batched because each is single-file with a committed
acceptance test, and two share documentation surfaces.

#16 (F-025) -- cog_gov_search() utility mode interpolated `name` straight
into regexp_matches() unescaped, while basket mode in the same file already
routed it through .escape_regex() with the comment "so `name` is treated as
a literal substring". Two failure modes, both HTTP 200 through the API:
a government could not be found by its own complete name when that name
contains a metacharacter (FREDONIA (BRISCOE) CITY returned nothing), and a
bare "." matched all 608 Wisconsin cities. Malformed pattern text reached
the engine as an error, which cog-api surfaced as a 500 -- reachable by
typing a real name one character at a time ("Athens-Clarke County (bal").

Utility mode now calls the escaper that already existed. Roxygen updated:
utility mode is documented as a literal case-insensitive substring match,
and the basket-mode "substring fallback" step no longer describes itself as
a regex either.

  BEHAVIOUR CHANGE worth flagging: anchored exact-match searches stop
  working, because there is no regex left to anchor. Two existing tests used
  "^BROWARD COUNTY$" and "^FLORIDA$" as their exact-match idiom; both now
  search for those characters literally. Updated to the bare names, which
  still resolve to exactly one row each once scoped by state/type (verified,
  not assumed). There is no exact-match option in utility mode any more --
  noted on the issue, since that is a real if small capability loss.

#15 (F-004) -- the raw Census files report thousands of dollars; this
package multiplies by 1000 and returns full US dollars. Correct, and already
stated in ?cog_spending / ?cog_revenue @return, in provenance, and in
cog-api's data-dictionary. Absent from every surface a reader meets FIRST.
Added to README.md as its own section and to both vignettes' openings.

The dangerous one is cog_explorer/CLAUDE.md, which states the opposite rule
("All raw `amt` values are in $1,000s") without scoping it to the raw column
-- a reader applying that to amt_nominal overstates by 1000x and gets a
plausible-looking number rather than an obvious error. Fixed there too; that
directory has no git remote, so it rides in no PR and is left uncommitted
for the owner.

#14 (F-021) -- .peer_summary_rows() computes stats::quantile() separately
inside each (year, spend_subtype, category) cell, so a summary_p50 row is
"the median peer's value in that one category", never "the value of the
median peer's total" -- the median peer for Police and for Fire are usually
different governments. Summing them across categories misstated a
total-spending band by -32.7% to +251.0% across 24 years, with a sign flip
at FY2012. The verb is right and its documented use (facet by role AND
category) is unaffected, so the fix is @return prose plus a worked snippet
showing the correct computation: sum each peer's own categories first, then
take the quantile of those per-government totals.

This is the R-side counterpart of cog-api#9, fixed on the API surface
earlier today; the wording is deliberately consistent across the two.

Note the phrase "not additive" has to stay on one roxygen source line --
the test greps the generated Rd, where a line wrap turns it into
"not   additive" and stops matching. Cost one red run to find.

man/ regenerated with roxygen 8.0.0 against a repo built with 7.3.3, so
cog_spending.Rd and DESCRIPTION were reverted -- their entire diff was
version churn (reindentation, RoxygenNote -> Config/roxygen2/version) with
no content change. The two Rd files kept carry only the edits above.

Suite: 629 pass / 0 fail / 3 skip (was 606/0/6). The three remaining skips
are #11, #12 and #13.

R/peers.R

@@ -133,7 +133,9 @@ cog_find_peers <- function(target_govid,
 #' [cog_find_peers()] result or a character vector of `canonical_govid`) and
 #' appends peer-distribution summary rows (`summary_p25`, `summary_p50`,
 #' `summary_p75`) so the result can be faceted by `role` in a single ggplot
-#' call.
+#' call. Those summary rows are quantiles **within each category**, not
+#' quantiles of each peer's total — see the `@return` section before summing
+#' them.
 #'
 #' @param target_govid Character scalar.
 #' @param peers A tibble from [cog_find_peers()] or a character vector of
@@ -155,6 +157,32 @@ cog_find_peers <- function(target_govid,
 #'   `attr(peers, "cohort_year")`; `NA` when `peers` was a bare character
 #'   vector). Provenance reports `verb = "cog_peer_compare"`, `peer_count`,
 #'   `cohort_year`, and `cohort_govids`.
+#'
+#'   **The `summary_*` rows are per-category quantiles: they are not additive.**
+#'   Each one is computed **within each `(year, spend_subtype,
+#'   category)` cell** across the peer set, so a `summary_p50` row is *the
+#'   median peer's value in that one category*, not *the value of the median
+#'   peer's total*. The median peer for Police and the median peer for Fire
+#'   are usually different governments, so summing `summary_*` rows across
+#'   categories does not give any peer's total and misstates the band it
+#'   appears to describe — measured at −32.7% to +251.0% across 24 years on
+#'   one cohort, with a sign flip at FY2012.
+#'
+#'   Facet by `role` **and** `category` (the documented use, and what the
+#'   rows are built for). For a genuine "median peer's total spending" line,
+#'   sum each peer's own categories first and take the quantile of those
+#'   per-government totals:
+#'
+#'   ```r
+#'   library(dplyr)
+#'   cmp |>
+#'     filter(role %in% c("target", "peer")) |>
+#'     group_by(year, role, canonical_govid) |>
+#'     summarise(total = sum(amt_per_capita_real, na.rm = TRUE), .groups = "drop") |>
+#'     filter(role == "peer") |>
+#'     group_by(year) |>
+#'     summarise(p50 = quantile(total, 0.5, na.rm = TRUE))
+#'   ```
 #' @export
 cog_peer_compare <- function(target_govid, peers, category, years,
                              per_capita = TRUE, adjust_to_year = NULL,

R/search.R

@@ -6,8 +6,11 @@
 #' the cross-vintage canonical-government registry. Operates in two modes:
 #'
 #' * **Utility mode** (single `name`, the original behavior): returns all
-#'   rows whose `gov_name` matches the regex case-insensitively, sorted by
-#'   `population_acs` descending. Useful for exploratory lookups.
+#'   rows whose `gov_name` contains `name` as a **literal, case-insensitive
+#'   substring**, sorted by `population_acs` descending. Useful for
+#'   exploratory lookups. Regex metacharacters in `name` are escaped, so a
+#'   government is findable by its own complete name even when that name
+#'   contains parentheses or a period.
 #' * **Basket mode** (`length(name) > 1`): resolves each input row to a
 #'   single canonical govid and returns a tibble in input order, suitable
 #'   for piping straight into [cog_spending()] / [cog_revenue()] /
@@ -19,7 +22,8 @@
 #' 1. Filter `canonical_fips_xwalk` by `state` and (if non-NA) `type`.
 #' 2. **Exact pass:** case-insensitive equality against `gov_name`.
 #'    Single hit -> resolved. Multiple -> step 4.
-#' 3. **Substring fallback:** case-insensitive regex against `gov_name`.
+#' 3. **Substring fallback:** case-insensitive literal substring against
+#'    `gov_name` (metacharacters escaped).
 #'    Single hit -> resolved (`match_method = "substring"`). Zero hits ->
 #'    `status = "no_match"`. Multiple hits -> step 4.
 #' 4. **Disambiguation:** if matches share one `govs_type`, pick the
@@ -48,7 +52,7 @@
 #'   [cog_spending()], [cog_revenue()].
 #' @examples
 #' \dontrun{
-#' # Utility mode — exploratory regex lookup
+#' # Utility mode — exploratory substring lookup
 #' cog_gov_search("broward", state = "FL")
 #'
 #' # Basket mode — resolve a known cohort
@@ -98,9 +102,16 @@ cog_gov_search <- function(name = NULL, state = NULL, type = NULL) {
     if (!is.character(name) || length(name) != 1L) {
       cli::cli_abort("`name` must be a length-1 character string.")
     }
+    # Escaped, so `name` is a literal case-insensitive substring -- the same
+    # treatment basket mode has always given it. Interpolating it raw made a
+    # government unfindable by its own name whenever that name contains a
+    # metacharacter (FREDONIA (BRISCOE) CITY), turned a bare "." into a
+    # match-everything wildcard, and let malformed pattern text reach the
+    # engine as an error -- which cog-api surfaced as a 500, reachable by
+    # typing a real name one character at a time (uscogdata#16, F-025).
     preds <- c(preds,
                sprintf("regexp_matches(gov_name, %s, 'i')",
-                       .sql_lit_chr(name)))
+                       .sql_lit_chr(.escape_regex(name))))
   }
   if (!is.null(state)) {
     st_fips <- .coerce_state_to_fips(state)
@@ -136,8 +147,9 @@ cog_gov_search <- function(name = NULL, state = NULL, type = NULL) {
 #' @noRd
 .escape_regex <- function(x) {
   # Backslash-escape POSIX regex metacharacters so `name` is treated as a
-  # literal substring in the DuckDB regexp_matches call (substring fallback
-  # only; utility-mode intentionally preserves regex behavior).
+  # literal substring in the DuckDB regexp_matches call. Used by BOTH modes:
+  # utility mode used to interpolate raw, which was a defect rather than a
+  # feature -- see the call site and uscogdata#16.
   gsub("([\\^$.|?*+(){}\\[\\]])", "\\\\\\1", x, perl = TRUE)
 }