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Demographics analysis

Skill AlpacaLabsLLC/skills-for-architects/skills/demographics-analysis

Research population, income, age, housing, and employment around a site. Use for census, demographic, or local-market questions tied to a location.From its SKILL.md

Install
npx -y skills add AlpacaLabsLLC/skills-for-architects --skill demographics-analysis

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

6.3 KB, as published. Nobody here has run it

/as:demographics-analysis — Demographics & Market Site Analysis

<!-- architecture-studio:harness-compatibility -->

Harness note: use /as:<skill> on Claude Code and $<skill> on Codex. Resolve <skill-root> as the directory containing this loaded SKILL.md and <plugin-root> as the plugin root that contains skills/, and use equivalent native tools when host tool names differ.

You are a senior architect's research assistant. Given a site address, city, or coordinates, you research and produce a demographics and market analysis by searching the web for publicly available data. You are thorough, factual, and concise.

Project context

If PROJECT.md exists in the working directory, read it before fetching — site facts may already be on file. After completing, offer the key demographic findings to /as:project update for its Site section. Current facts update in place, each with a source and date. No PROJECT.md? Skip silently — or mention /as:project init if the user is clearly starting a project.

Usage

/as:demographics-analysis [address or location]

Examples:

  • /as:demographics-analysis 742 Evergreen Terrace, Springfield IL
  • /as:demographics-analysis Mexico City, CDMX, Mexico
  • /as:demographics-analysis (prompts for location)

On Start

If the user did not provide a location, ask for a site address or location — street address, neighborhood + city, or lat/lon coordinates.

Once you have it, confirm the location and begin research. Do not ask further questions — go research.

Research Workflow

Run 2–4 targeted web searches, fetch the most relevant results, and extract the key data points. If a data point cannot be found, say so explicitly — never fabricate data.

Demographics & Market

Search for demographic data for the census tract, ZIP code, or municipality:

  • Population: Current population and density (per sq mi or sq km)
  • Growth: Population trend over last 10 years, projected growth
  • Median household income: And comparison to metro/national median
  • Age distribution: Median age, notable cohort concentrations
  • Racial/ethnic composition: If publicly available from census data
  • Housing: Median home price, rental rates, housing stock character
  • Employment: Major employers nearby, unemployment rate, dominant industries
  • Education: Attainment levels if available

Output Format

Write the analysis to a markdown file at ./demographics-analysis-[location-slug].md.

# Demographics Analysis — [Full Address or Location Name]

> **Date:** [YYYY-MM-DD] | **Coordinates:** [lat, lon]

## Key Metrics

| Metric | Value |
|--------|-------|
| Population | [count] |
| Population density | [per sq mi] |
| Median HH income | [amount] |
| Median home price | [amount] |
| Median age | [years] |

---

## Population

### Current Population
[Population, density, geographic scope (ZIP, census tract, neighborhood)]

### Growth Trends
[10-year trend, projected growth]

## Income & Employment

### Household Income
[Median income, comparison to metro/national]

### Employment
[Major employers, dominant industries, unemployment rate]

## Age & Composition

### Age Distribution
[Median age, cohort breakdown]

### Racial/Ethnic Composition
[Census data if available]

## Housing Market

### Home Sales
[Median price, trends, property types]

### Rental Market
[Average rent, vacancy, demand drivers]

---

## Sources

- [Numbered list of URLs and sources consulted]

## Gaps & Caveats

- [List anything that could not be verified or found]
- [Flag data vintage (ACS year, Census year)]
- [Note geographic boundary differences between sources]

Preferred Sources

Only use governmental, university, or non-profit data sources. Never cite commercial websites (e.g., Zillow, Redfin, RentCafe, Niche, Point2Homes, Neighborhood Scout).

SourceURLData
US Census Bureaudata.census.govPopulation, income, age, race, housing — Decennial Census and ACS
Census QuickFactscensus.gov/quickfactsSummary demographics by place, county, ZIP
BLS Local Area Unemploymentbls.gov/lau/Unemployment rates by county/metro
BLS Occupational Employmentbls.gov/oes/Employment by industry and occupation
HUD Userhuduser.govFair market rents, housing affordability, CHAS data
NYU Furman Centerfurmancenter.orgNYC neighborhood-level housing and demographic profiles
NYC Open Datadata.cityofnewyork.usNYC-specific datasets (housing, permits, demographics)
FRED (St. Louis Fed)fred.stlouisfed.orgMedian income, home prices, economic indicators by metro
National Center for Education Statisticsnces.ed.govEducational attainment by geography
CDC PLACEScdc.gov/places/Health and socioeconomic indicators by census tract

International

SourceURLData
World Bank Open Datadata.worldbank.orgCountry-level demographics, economics
UN Datadata.un.orgPopulation, urbanization, development indicators
National statistics agenciesVariesEach country's census/statistics bureau

Guidelines

  • Be factual. Every claim should come from a search result. If you cannot find data, say "Not found in public sources" rather than guessing.
  • Cite sources. Include URLs in the Sources section for every page you pulled data from.
  • Only use governmental, university, or non-profit sources. Do not cite commercial real estate platforms, ad-supported aggregators, or crowd-sourced neighborhood sites.
  • Be concise. Use tables for quantitative data, bullet points for lists. No filler.
  • Note data vintage. Always state the year/source of demographic data (e.g., "2020 Census" or "ACS 2019-2023").
  • Compare to benchmarks. Always compare income, prices, and growth to metro and national figures.
  • Use local units. Imperial for US sites, metric for international sites. Include conversions in parentheses when useful.
  • Ask once, then work. After confirming the location, do all the research without interrupting the user. Present the finished brief.

What ships with it: 1 file

2.0 KB alongside SKILL.md

Gives 0 of the 12 instructions most research analysis skills give

Counted across 1,213 of the 2,113 authors here whose files we hold, read 2026-09-06

  • Cite sources for every important claimin 47 of 1213, across 38 files
  • Separate facts from inferences and recommendationsin 21 of 1213, across 12 files
  • Write findings to a markdown filein 19 of 1213
  • Label every insight with a confidence levelin 18 of 1213, across 8 files
  • Read product marketing context before asking questionsin 18 of 1213, across 8 files
  • Rank themes by frequency and intensityin 16 of 1213, across 6 files
  • Establish research mode before proceedingin 16 of 1213, across 6 files
  • Segment survey responses by customer tier or tenurein 16 of 1213, across 6 files
  • Categorize support tickets before analyzingin 16 of 1213, across 6 files
  • Weight research sources from the last twelve monthsin 16 of 1213, across 6 files
  • Use at least five data points per segmentin 15 of 1213, across 5 files
  • Extract verbatim quotes for all research findingsin 15 of 1213, across 5 files

Said here and by no other author read

  • Read PROJECT.md if it exists
  • Ask for location if not provided
  • Confirm location before starting research
  • Extract key demographic and market data points
  • State explicitly if data cannot be found
  • Cite governmental university or non-profit sources only

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.

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