List every dataset (stat) StatsMapped tracks for one country ('ireland' or 'united-kingdom'), with its key, human label, and which geography levels it can be shown at. Ireland and the UK track genuinely different datasets -- call this for the right country before assuming a stat_key exists there. Call this first to find the right stat_key for rank_areas -- for get_dataset_for_area, use list_area_datasets instead, which returns the series_key that call actually needs.

List every geography at one boundary level, for one country ('ireland' or 'united-kingdom'). level defaults to "county" (Ireland's 26 counties); the UK's own primary level is "lad" (local authority districts), not "county". Other levels exist per country (e.g. Ireland's "local_authority", "garda_division") -- see a dataset's own compatible_levels from list_datasets for which levels a given stat is actually published at. Returns each area's id (used by list_area_datasets/get_dataset_for_area, always paired with the SAME country) and name.

List every dataset available for one area (e.g. "county:kerry" for Ireland, "uk:lad:e09000033" for the UK), with its latest figure, year-on- year change, and caveat labels only (not full caveat text -- call get_dataset_for_area for the full detail on any one dataset that matters). Area ids come from list_areas -- country must match whichever country that call used, or this simply 404s ("unknown geography").

Full detail for one dataset in one area: the latest figure, a written summary, full caveat text, and (if history_months is set) recent history. dataset is a series_key from list_area_datasets' own response. history_months means actual months of history (0 = everything) -- e.g. 24 returns 2 years of an annual series, not 24 years. country must match area_id's own country.

Rank every area at one geography level by its latest figure for one stat, for one country -- e.g. "which counties have the highest median sale price" (country="ireland") or "which local authorities award the most single-bid contracts" (country="united-kingdom"). stat_key comes from list_datasets(country=...) for the SAME country -- Ireland and the UK track different stats. level omitted uses this ranking's own default level; pass one of that dataset's own compatible_levels for a different one -- a level this ranking doesn't have registered returns an empty list rather than an error.

Where the underlying stat has no honest per-area denominator (crime, homelessness, live_register and similar -- StatsMapped's own RANKING_NO_DENOMINATOR_STATS), each row's rate_per_1000 is the real figure to rank/compare by, not latest_value, which is a raw count dominated by area population size. Always carry forward every entry in caveats when using a row in an answer -- the same caveats StatsMapped's own ranking pages and chat both attach to these figures.

List every registered cross-dataset comparison pair for one country ('ireland' or 'united-kingdom') -- e.g. "median sale price vs new dwelling completions per 1,000 residents". A small, hand-curated set, not an arbitrary-pair engine: pass one of the returned pair_key values to get_comparison for the real correlation and axis detail.

Full detail for one registered comparison pair: each axis's label, unit and publisher, the correlation stats (r, rho, and a leave-one-out sensitivity range naming the single most influential area), and caveats. pair_key comes from list_comparisons(country=...) for the SAME country.

Does StatsMapped have a registered, hand-vetted comparison between these two stats ('ireland' or 'united-kingdom')? Registry-backed only -- never computes a fresh correlation for an arbitrary pair. Both stat_keys come from list_datasets(country=...) for the SAME country. A comparable: false result is normal and expected for most pairs (the registry is small and hand-curated) -- treat it as StatsMapped saying it has not vetted a relationship between these two stats, not as an error to route around.

Definition, methodology and standing caveats for ONE stat ('ireland' or 'united-kingdom') -- never a current figure. Call this when the question is about what a metric MEANS or how it's measured ("how is the claimant count defined", "is this a mean or a median"), not about a specific area's value -- get_dataset_for_area/rank_areas already answer that. stat_key comes from list_datasets(country=...) for the SAME country.