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From nz-skills
Queries official NZ child poverty statistics from Stats NZ: nine CPRA measures, national rates (2007–2025), and breakdowns by region, ethnicity and disability.
npx claudepluginhub thecolab-ai/.skills --plugin nz-skillsHow this skill is triggered — by the user, by Claude, or both
Slash command
/nz-skills:child-poverty-nzThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Read-only CLI over Stats NZ's annual Child Poverty Reduction Act (CPRA) data
Queries Stats NZ Household Economic Survey data for material hardship, income adequacy, housing affordability, low-income household counts, and Gini coefficient by region or ethnicity, with confidence intervals.
Queries public statistical data from Data Commons (demographics, economics, health, environment) via the Python API v2. Use for population, GDP, unemployment, disease prevalence, and geographic entity resolution.
Finds the authoritative official source for any statistical indicator, including where to get the latest figures and what to watch for.
Share bugs, ideas, or general feedback.
Read-only CLI over Stats NZ's annual Child Poverty Reduction Act (CPRA) data releases. Each release is a public ZIP of UTF-8 CSVs (no API key, no login, no bot challenge). The CLI auto-discovers the latest release from the Stats NZ CSV-files index, downloads the ZIP in memory, and parses the national and disaggregated data files with the Python standard library only.
The nine measures use codes MEASA–MEASJ (Stats NZ skips MEASD). The three
primary legislated measures are MEASA (income below 50% of the median
before housing costs, moving line), MEASB (below 50% after housing costs,
anchored line) and MEASC (material hardship, DEP-17, lacking 6+ of 17
items). MEASI is severe material hardship (lacking 9+ items) — a subset of
MEASC — and MEASJ is the combined low-income-and-hardship measure.
Use this when the task involves:
Do not use this for: household-income/housing-cost statistics, benefit payment records, the public housing register, or non-NZ poverty data.
Run with python3 scripts/cli.py <command>. Every command supports --json.
measures [--json] — list the nine CPRA measure codes with plain-English names.national --measure CODE [--year Y] [--from Y] [--to Y] [--json] — proportion (%), number (000s), annual change and child population for a measure, with confidence intervals. Defaults to MEASA, full 2007-2025 range.latest [--json] — the most recent year's headline proportion + CI for all nine measures.breakdown --measure CODE --by region|ethnicity|disability [--year Y] [--json] — disaggregated proportion/number across the demographic codes (2019-2025).trend --measure CODE [--demographic CODE] [--json] — full time series for charting; pass a demographic code (e.g. REGC02, ETHG02, DISD01) for a disaggregated series.releases [--json] — scrape the Stats NZ CSV-files index to list available child-poverty releases and their ZIP URLs.Errors print to stderr and exit non-zero.
# Headline picture for the latest year, all nine measures
python3 scripts/cli.py latest --json
# Primary measure (BHC<50%) national trend, last three years
python3 scripts/cli.py national --measure MEASA --from 2023 --to 2025
# Material hardship among children by disability status
python3 scripts/cli.py breakdown --measure MEASC --by disability --json
# Child poverty by ethnicity for the primary measure
python3 scripts/cli.py breakdown --measure MEASA --by ethnicity
# Māori child poverty time series for charting
python3 scripts/cli.py trend --measure MEASA --demographic ETHG02 --json
# Discover the latest release ZIP
python3 scripts/cli.py releases --json
*_lower_ci / *_upper_ci) alongside a rate, not just the point estimate.NA = no prior-year data (change not applicable); cells may be suppressed (S) for confidentiality when fewer than six units contribute.scripts/smoke_test.py for a live check.references/api-notes.md.