firefrost-gaming/antigravity-skills-reference

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sickn33 054565490e meta(skills): Backfill risk and source metadata

Add a conservative metadata fixer for missing risk and source fields,
cover it with tests, and backfill the remaining skills using explicit
source inference only when the provenance is clear. Fall back to the
repo-documented defaults when the file does not support a stronger claim.

Refs #365

2026-03-20 09:17:09 +01:00

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name, description, risk, source

name	description	risk	source
hugging-face-dataset-viewer	Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.	unknown	community

Hugging Face Dataset Viewer

Use this skill to execute read-only Dataset Viewer API calls for dataset exploration and extraction.

Core workflow

Optionally validate dataset availability with /is-valid.
Resolve config + split with /splits.
Preview with /first-rows.
Paginate content with /rows using offset and length (max 100).
Use /search for text matching and /filter for row predicates.
Retrieve parquet links via /parquet and totals/metadata via /size and /statistics.

Defaults

Base URL: https://datasets-server.huggingface.co
Default API method: GET
Query params should be URL-encoded.
offset is 0-based.
length max is usually 100 for row-like endpoints.
Gated/private datasets require Authorization: Bearer <HF_TOKEN>.

Dataset Viewer

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.
Keep filtering and searches read-only and side-effect free.

Querying Datasets

Use npx parquetlens with Hub parquet alias paths for SQL querying.

Parquet alias shape:

hf://datasets/<namespace>/<repo>@~parquet/<config>/<split>/<shard>.parquet

Derive <config>, <split>, and <shard> from Dataset Viewer /parquet:

curl -s "https://datasets-server.huggingface.co/parquet?dataset=cfahlgren1/hub-stats" \
  | jq -r '.parquet_files[] | "hf://datasets/\(.dataset)@~parquet/\(.config)/\(.split)/\(.filename)"'

Run SQL query:

npx -y -p parquetlens -p @parquetlens/sql parquetlens \
  "hf://datasets/<namespace>/<repo>@~parquet/<config>/<split>/<shard>.parquet" \
  --sql "SELECT * FROM data LIMIT 20"

SQL export

CSV: --sql "COPY (SELECT * FROM data LIMIT 1000) TO 'export.csv' (FORMAT CSV, HEADER, DELIMITER ',')"
JSON: --sql "COPY (SELECT * FROM data LIMIT 1000) TO 'export.json' (FORMAT JSON)"
Parquet: --sql "COPY (SELECT * FROM data LIMIT 1000) TO 'export.parquet' (FORMAT PARQUET)"

Creating and Uploading Datasets

Use one of these flows depending on dependency constraints.

Zero local dependencies (Hub UI):

Create dataset repo in browser: https://huggingface.co/new-dataset
Upload parquet files in the repo "Files and versions" page.
Verify shards appear in Dataset Viewer:

curl -s "https://datasets-server.huggingface.co/parquet?dataset=<namespace>/<repo>"

Low dependency CLI flow (npx @huggingface/hub / hfjs):

Set auth token:

export HF_TOKEN=<your_hf_token>

Upload parquet folder to a dataset repo (auto-creates repo if missing):

npx -y @huggingface/hub upload datasets/<namespace>/<repo> ./local/parquet-folder data

Upload as private repo on creation:

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.

When to Use

Use this skill when tackling tasks related to its primary domain or functionality as described above.

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