Install
openclaw skills install naver-datalab-cliKorean search-keyword and shopping-trend analytics via the official NAVER DataLab API (openapi.naver.com/v1/datalab/*). Six subcommands wrapping 통합 검색어 트렌드 and 쇼핑인사이트 (분야별, 분야 내 키워드, 디바이스/성별/연령대 분포). Use when researching Korean consumer demand, planning SEO/content for the naver.com search market, comparing keyword popularity over time, building K-pop / K-beauty / K-commerce trend dashboards, or filling the gap that Google Trends leaves on Korean queries. Pairs with naver-papago-translate (translate insights), tistory-api-cli / velog-cli (publish trend posts), and kr-holiday-cli (align campaigns with KR calendar). Free tier (1k req/day for shopping insights, 25k req/day for search trends).
openclaw skills install naver-datalab-cliCommand-line wrapper for the NAVER DataLab Open API — Korea's primary search-keyword and shopping-insight trend service. The Korean equivalent of Google Trends, with two key advantages on KR-market analysis:
Six subcommands, one per official endpoint:
| Command | Endpoint | Purpose |
|---|---|---|
scripts/search.sh | /v1/datalab/search | 통합 검색어 트렌드 — compare up to 5 keyword groups (each with up to 20 synonyms) over time. |
scripts/shop-cat.sh | /v1/datalab/shopping/categories | 쇼핑인사이트 분야별 트렌드 — compare shopping-category click volumes. |
scripts/shop-keyword.sh | /v1/datalab/shopping/category/keywords | 분야 내 키워드 트렌드 — within one category, compare keyword interest. |
scripts/shop-device.sh | /v1/datalab/shopping/category/device | Device split (pc / mo) for one category. |
scripts/shop-gender.sh | /v1/datalab/shopping/category/gender | Gender split (f / m) for one category. |
scripts/shop-age.sh | /v1/datalab/shopping/category/age | Age split (10/20/30/40/50/60) for one category. |
All output is JSONL (one row per period per group) so it pipes directly into jq, csvkit, pandas, or downstream skills.
google-trends or platform-specific skills.naver-search (existing ClawHub skill).export NAVER_CLIENT_ID='abcdEFG12345'
export NAVER_CLIENT_SECRET='AbCdEfGhIj'
bash, curl, jq (default on macOS/Linux).Free-tier quota: 25,000 req/day for /v1/datalab/search, 1,000 req/day for shopping endpoints.
search — 통합 검색어 트렌드Compare up to 5 keyword groups over a time range:
scripts/search.sh \
--start 2024-01-01 --end 2024-12-31 --time-unit month \
--group "한국어:한국어,한글" \
--group "영어:영어,English"
Optional filters: --device pc|mo, --gender f|m, --ages 1,2,3 (1=under 12, 2=13-18, 3=19-24, 4=25-29, 5=30-34, 6=35-39, 7=40-49, 8=50-59, 9=60+). Up to 5 --group blocks; each group has 1-20 keywords.
Output (one record per group per period):
{"groupName":"한국어","period":"2024-01-01","ratio":78.32}
shop-cat — 쇼핑인사이트 분야별 트렌드scripts/shop-cat.sh \
--start 2024-01-01 --end 2024-12-31 --time-unit month \
--category "패션의류:50000000" \
--category "화장품/미용:50000002"
Same filters as search. Up to 3 categories per call. Category IDs come from https://datalab.naver.com/shoppingInsight/sCategory.naver.
shop-keyword — 분야 내 키워드 트렌드Drill into one category:
scripts/shop-keyword.sh \
--start 2024-06-01 --end 2024-12-31 --time-unit week \
--category 50000000 \
--keyword "원피스:원피스" \
--keyword "치마:치마,스커트"
shop-device / shop-gender / shop-ageSingle-category breakdown by demographic:
scripts/shop-device.sh --start 2024-01-01 --end 2024-06-30 --time-unit month --category 50000000
scripts/shop-gender.sh --start 2024-01-01 --end 2024-06-30 --time-unit month --category 50000000
scripts/shop-age.sh --start 2024-01-01 --end 2024-06-30 --time-unit month --category 50000000
Output rows include the demographic dimension:
{"period":"2024-01-01","group":"pc","ratio":42.1}
{"period":"2024-01-01","group":"mo","ratio":100.0}
See examples/ for canned recipes:
examples/yearly-search.sh — yearly comparison "전기차 vs 하이브리드".examples/k-beauty-by-age.sh — 화장품/미용 demographic split.examples/seasonal-campaign.sh — find "수능 도시락" peak month.timeUnit accepts date, week, month — not day. (Date with daily granularity is date.)period returned by daily/weekly is the start of the bucket, not the end.category (singular) for the breakdown calls but category (array of objects) for categories. The wrapper hides this.200 OK with empty results[].data. The wrapper emits no JSONL lines for that group; check exit status and stderr.ratio is relative, not absolute. The peak point in the entire response is normalized to 100.| Code | Name |
|---|---|
| 50000000 | 패션의류 |
| 50000001 | 패션잡화 |
| 50000002 | 화장품/미용 |
| 50000003 | 디지털/가전 |
| 50000004 | 가구/인테리어 |
| 50000005 | 출산/육아 |
| 50000006 | 식품 |
| 50000007 | 스포츠/레저 |
| 50000008 | 생활/건강 |
Full tree: https://datalab.naver.com/shoppingInsight/sCategory.naver.
naver-papago-translate — translate the trend report into EN/JP/ZH for cross-market briefs.tistory-api-cli / velog-cli — publish weekly Korean-trend posts.kr-holiday-cli — overlay holiday/business-day calendar to interpret seasonal spikes.kakao-local-cli + juso-address-cli — geo-resolve any place names that emerge from trend keywords.