Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/ranbot-ai/awesome-skills --skill hugging-face-dataset-viewer명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
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Generate project-specific AGENTS.md and companion rules by analyzing a codebase. Supports full, minimal, update, and dry-run modes with package-manager detection, monorepos, backups, managed blocks, c
Run protected AAS maintainer sweeps, PR merge batches, canonical sync, Core preview checks, and scripted releases. Use for repository maintenance, main alignment, CLI/MCP/Workbench changes, or release
Provision backend infra through Cohesivity (cohesivity.ai): Postgres, hosting, auth, storage, and AI model APIs over one HTTP API. Use when a .cohesivity file exists or a project needs a backend.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | hugging-face-dataset-viewer |
| description | Hugging Face Dataset Viewer |
| category | Document Processing |
| source | antigravity |
| tags | ["api","claude","ai","agent","workflow","document","security","cro"] |
| url | https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/hugging-face-dataset-viewer |
Use this skill when you need hugging Face Dataset Viewer.
Use this skill to execute read-only Dataset Viewer API calls for dataset exploration and extraction.
/is-valid.config + split with /splits./first-rows./rows using offset and length (max 100)./search for text matching and /filter for row predicates./parquet and totals/metadata via /size and /statistics.https://datasets-server.huggingface.coGEToffset is 0-based.length max is usually 100 for row-like endpoints.Authorization: Bearer <HF_TOKEN>.Validate dataset: /is-valid?dataset=<namespace/repo>List subsets and splits: /splits?dataset=<namespace/repo>Preview first rows: /first-rows?dataset=<namespace/repo>&config=<config>&split=<split>Paginate rows: /rows?dataset=<namespace/repo>&config=<config>&split=<split>&offset=<int>&length=<int>Search text: /search?dataset=<namespace/repo>&config=<config>&split=<split>&query=<text>&offset=<int>&length=<int>Filter with predicates: /filter?dataset=<namespace/repo>&config=<config>&split=<split>&where=<predicate>&orderby=<sort>&offset=<int>&length=<int>List parquet shards: /parquet?dataset=<namespace/repo>Get size totals: /size?dataset=<namespace/repo>Get column statistics: /statistics?dataset=<namespace/repo>&config=<config>&split=<split>Get Croissant metadata (if available): /croissant?dataset=<namespace/repo>Pagination pattern:
curl "https://datasets-server.huggingface.co/rows?dataset=stanfordnlp/imdb&config=plain_text&split=train&offset=0&length=100"
curl "https://datasets-server.huggingface.co/rows?dataset=stanfordnlp/imdb&config=plain_text&split=train&offset=100&length=100"
When pagination is partial, use response fields such as num_rows_total, num_rows_per_page, and partial to drive continuation logic.
Search/filter notes:
/search matches string columns (full-text style behavior is internal to the API)./filter requires predicate syntax in where and optional sort in orderby.For CLI-based parquet URL discovery or SQL, use the hf-cli skill with hf datasets parquet and hf datasets sql.
Use one of these flows depending on dependency constraints.
Zero local dependencies (Hub UI):
https://huggingface.co/new-datasetcurl -s "https://datasets-server.huggingface.co/parquet?dataset=<namespace>/<repo>"
Low dependency CLI flow (npx @huggingface/hub / hfjs):
export HF_TOKEN=<your_hf_token>
npx -y @huggingface/hub upload datasets/<namespace>/<repo> ./local/parquet-folder data
npx -y @huggingface/hub upload datasets/<namespace>/<repo> ./local/parquet-folder data --private
After upload, call /parquet to discover <config>/<split>/<shard> values for querying with @~parquet.
The Hub supports raw agent session traces from Claude Code, Codex, and Pi Agent. Upload them to Hugging Face Datasets as original JSONL files and the Hub can auto-detect the trace format, tag the dataset as Traces, and enable the trace viewer for browsing sessions, turns, tool calls, and model responses. Common local session directories:
~/.claude/projects~/.codex/sessions~/.pi/agent/sessionsDefault to private dataset repos because traces can contain prompts, file paths, tool outputs, secrets, or PII. Preserve the raw .jsonl files and nest them by project/cwd instead of uploading every session at the dataset root.
hf repos create <namespace>/<repo> --type dataset --private --exist-ok
hf upload <namespace>/<repo> ~/.codex/sessions codex/<project-or-cwd> --type dataset