Stats NZ Census
SkillFiles & storageQuery official public 2018 Stats NZ Census national-highlights CSV tables while preserving dimensions and suppression/status markers. No API key required.
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Then ask your AI: use the Stats NZ Census skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
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No other account needed.
Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
What this skill tells your AI
The instructions your AI receives, as published by thecolab-ai/.skills in skills/stats-nz-census/SKILL.md and read by Ahel’s review.
Query the official 2018 Census totals by topic – national highlights CSV archive. This is a narrow, standalone public aggregate-data connector; it does not use authenticated Stats NZ surfaces or Census microdata.
Use this when
- A user needs a published 2018 Census national-highlight count by topic/category.
- You need to discover the topic tables in the official CSV download.
- Another tool needs bounded JSON that retains the table's dimensions and source markers.
Do not use this for
- 2023 Census observations, subnational tables, meshblock data, or time-series comparisons.
- Restricted/confidentialised unit records or authenticated Stats NZ surfaces.
- Estimation, interpolation, de-rounding, cross-tabulation, or joining unlike dimensions.
No 2023 values are implied: the public 2023 product finder is metadata, while detailed API access may require a subscription key.
CLI
# List available topic tables (the positional topic is optional)
python3 skills/stats-nz-census/scripts/cli.py --json
# Query the common positional topic path
python3 skills/stats-nz-census/scripts/cli.py age-single-years --limit 10 --json
python3 skills/stats-nz-census/scripts/cli.py ethnic-group-total-responses --category european --json
python3 skills/stats-nz-census/scripts/cli.py age-single-years --measure Census_usually_resident --json
Arguments:
[TOPIC]: case-insensitive substring of a published CSV member/topic slug. Omit it to list topics.--category TEXT: filter category code or label without changing either dimension.--measure TEXT: filter a published measure heading.--limit N: return 1–100 observations (default 20).--json: emit the repository result envelope; otherwise print concise text.
An unmatched topic or filter is a successful empty result with a warning. Source/schema failures are never reported as empty data.
Data rules
- Preserve
category_dimension,category_code,category_label, andmeasureseparately. - Preserve
raw_value,value_status, andsource_symbol; suppression/confidentiality/missing markers remainvalue: nulland are never changed to zero. - Retain the source member and source row for traceability.
- Treat figures as published, rounded national aggregate counts; do not infer hidden values.
- Attribute reported figures to Stats NZ and include the source URL.
Read references/source-notes.md for scope and status-marker details. Parser fixtures are in tests/fixtures/. Run scripts/test_contract.py and scripts/smoke_test.py after changes.
Signals
- GitHub stars
- 31
- Forks
- 6
- Last commit
- Oct 2026
Ahel review
K6low
bundled executables the agent is told to run
Automated review, not a security audit. Ruleset v1+k2.
Advanced
- Item type
- skill
- Key
stats-nz-census- Source
- github.com/thecolab-ai/.skills
github.com/thecolab-ai/.skills