Data & analysis

crawlora-datasets

Try it

Queries Crawlora's pre-built hosted datasets — Airbnb markets, App Store/Google Play apps, GitHub/Instagram/X users, job postings, US housing markets, Google Maps businesses, Goodreads, PitchBook, Steam, TrustMRR, Product Hunt, SEC companies, tech-stack, and more — via search/facets/item/nearby endpoints, returning clean JSON without live-crawling each platform. Use when the user wants bulk or aggregate analysis, to search a pre-indexed corpus, to facet/filter a large population, or to look up one record by its dataset id, instead of scraping pages one at a time.

What it does

Queries Crawlora's pre-built hosted datasets — Airbnb markets, App Store/Google Play apps, GitHub/Instagram/X users, job postings, US housing markets, Google Maps businesses, Goodreads, PitchBook, Steam, TrustMRR, Product Hunt, SEC companies, tech-stack, and more — via search/facets/item/nearby endpoints, returning clean JSON without live-crawling each platform. Use when the user wants bulk or aggregate analysis, to search a pre-indexed corpus, to facet/filter a large population, or to look up one record by its dataset id, instead of scraping pages one at a time.

The skill document

Crawlora hosted datasets

Query Crawlora's own pre-crawled, pre-indexed datasets — search, facet, and fetch-by-id over corpora Crawlora already built and refreshes on a schedule. This is different from the other skills in this repo: those hit a live per-platform endpoint (one request, one page); this skill hits a search index over millions of already-collected records, so it's the right tool for population-level questions ("how many", "top N by X", "everything matching Y") rather than one-off lookups.

When to use this skill

  • "How many / what share of X match Y?" — facet/aggregate questions.
  • "Find all X with property Y" (e.g. jobs paying > $150k, apps with 4.5+ rating, GitHub users near a city, houses in a metro).
  • "Give me the full list of Z" instead of one record — bulk/list research.
  • Any of: Airbnb markets, app-store apps/reviews/charts, GitHub/Instagram/X users, job postings + which companies are hiring, US housing markets (Redfin-sourced), Google Maps businesses, Goodreads authors/books, Apple Podcasts shows, Chrome Web Store extensions, PitchBook companies/funds/ investors/advisors/LPs, PlayStation games, Product Hunt makers/products/ trends, Reddit trending, SEC companies + institutional positions, Steam games/prices/playercounts/reviews/news/achievements/charts, TrustMRR startups, journalists, Numbeo cost-of-living cities/countries, website tech-stack.
  • Prefer the platform-specific skill instead when the job is "look up this one profile/listing right now" (e.g. youtube-research, movie-tv-research) — datasets are refreshed periodically, not real-time.

Setup (one-time)

  • Get a free Crawlora API key (2,000 credits/mo, no card) at https://crawlora.net.
  • export CRAWLORA_API_KEY=sk_your_key_here
  • All requests: x-api-key: $CRAWLORA_API_KEY against https://api.crawlora.net/api/v1. Missing/invalid key → 401.

How it works

Every dataset follows the same shape under /datasets//...:

  1. DiscoverGET /datasets lists every available dataset id and its capabilities (search / facets / item / nearby).
  2. SearchGET /datasets//search full-text + filtered search; paginate with page/size (see reference/endpoints.md per dataset).
  3. FacetGET /datasets//facets returns aggregate breakdowns across a dataset's facetable fields at once (e.g. the jobs dataset returns top companies, department, location, seniority, remote share, and more in one call) — use for "how many / breakdown by X" questions.
  4. ItemGET /datasets//items/{id} fetches one record by its dataset key (varies per dataset: login, username, slug, cik, appid, domain, region_type/table_id, …).
  5. Nearby — where supported (airbnb-markets, github-users, google-map-businesses, jobs) — GET /datasets//nearby finds records near a lat/lon within radius_km.

Full endpoint list, per-dataset ids, and params: reference/endpoints.md.

Calling the API

# List every dataset id and what it supports:
scripts/crawlora.sh /datasets | jq '.'

# Search the jobs dataset (all companies' live postings):
scripts/crawlora.sh /datasets/jobs/search q="staff engineer" location="remote" | jq '.'

# Facet: hiring-market breakdown (top companies, seniority, remote share, ...):
scripts/crawlora.sh /datasets/jobs/facets | jq '.'

# Item: one GitHub user by login:
scripts/crawlora.sh /datasets/github-users/items/torvalds | jq '.'

# Nearby: GitHub users within 50km of a coordinate (radius in meters):
scripts/crawlora.sh /datasets/github-users/nearby lat=37.7749 lon=-122.4194 radius_m=50000 | jq '.'

Raw curl fallback:

curl -fsS -H "x-api-key: $CRAWLORA_API_KEY" \
  "https://api.crawlora.net/api/v1/datasets/steam-games/search?q=roguelike" | jq '.'

Endpoint reference

See reference/endpoints.md for every dataset id, its search/facets/item/nearby endpoints, and params.

Examples

  • Hiring-market pulse: /datasets/jobs/facets for the aggregate breakdown (top companies, seniority, remote share), then /datasets/jobs/companies to see which employers are actively posting.
  • App-store landscape scan: /datasets/apps/search filtered by category and rating, then /datasets/apps-reviews/search for the sentiment behind the top results.
  • Startup revenue leaderboard: /datasets/trustmrr/search sorted by MRR, then /datasets/trustmrr/history/{slug} for one company's trend line.
  • Housing-market snapshot: /datasets/housing-markets/search for a metro, then /datasets/housing-markets/items/{region_type}/{table_id} for the full monthly series.

Notes & limits

  • Credits / pay-on-success: billed only on 2xx; free tier 2,000 credits/mo. Key at https://crawlora.net.
  • Public data only — every dataset is built from public sources.
  • Security: key lives in CRAWLORA_API_KEY only — never hardcode, query-param, or commit it.
  • Datasets refresh on a schedule (daily/weekly depending on source) — not real-time. For a live single-record lookup, prefer the matching platform-specific skill in this repo (e.g. job-market-research, movie-tv-research) instead.
  • Results are paginated (page/size) — walk pages for full coverage.

Related skills

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