Agent skill · Testing & QA

arize-dataset

Creates, manages, and queries Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI. Use when the user needs test data, evaluation examples, or mentions create dataset, list datasets, export dataset, append examples, dataset version, golden dataset, or test set.

GitHub68,948★ · +463/wk · 2 repos on radarProfile →
copilotMIT
Install
npx skills add github/awesome-copilot --skill arize-dataset --agent copilot

Same command for any agent — swap --agent for claude-code, codex, cursor.

Facts
Files in the skill folder: 3
SKILL.md size: 15 KB
Bundled scripts: none
Version: 1.0
Declared author: arize
Requires: Requires the ax CLI and a configured Arize profile.
Path: skills/arize-dataset/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 37,432 · +281 this week
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Arize Dataset Skill > **`SPACE`** — All `--space` flags and the `ARIZE_SPACE` env var accept a space **name** (e.g., `my-workspace`) or a base64 space **ID** (e.g., `U3BhY2U6...`). Find yours with `ax spaces list`. ## Concepts - **Dataset** = a versioned collection of examples used for evaluation and experimentation - **Dataset Version** = a snapshot of a dataset at a point in time; updates can be in-place or create a new version - **Example** = a single record in a dataset with arbitrary user-defined fields (e.g., `question`, `answer`, `context`) - **Space** = an organizational container; datasets belong to a space System-managed fields on examples (`id`, `created_at`, `updated_at`) are auto-generated by the server -- never include them in create or append payloads. ## Prerequisites Proceed directly with the task — run the `ax` command you need. Do NOT check versions, env vars, or profiles upfront. If an `ax` command fails, troubleshoot based on the error: - `command not found` or version error → see references/ax-setup.md - `401 Unauthorized` / missing API key → run `ax profiles show` to inspect the current profile. If the profile is missing or the API key is wrong, follow refe

What's inside
Steps it walks through
  1. Concepts
  2. Prerequisites
  3. List Datasets: ax datasets list
  4. Flags
  5. Get Dataset: ax datasets get
  6. Response fields
  7. Export Dataset: ax datasets export
  8. Create Dataset: ax datasets create
  9. Passing data via stdin
  10. Supported file formats
  11. Append Examples: ax datasets append
  12. Inline JSON (agent-friendly)
  13. From a file
  14. To a specific version
Ships with 2 files
  • references/ax-profiles.md
  • references/ax-setup.md
Commands it runs
ax datasets list
ax datasets list --space SPACE --limit 20
ax datasets list --cursor CURSOR_TOKEN
ax datasets list -o json
ax datasets get NAME_OR_ID
ax datasets get NAME_OR_ID -o json
ax datasets get NAME_OR_ID --space SPACE   # required when using dataset name instead of ID
ax datasets export NAME_OR_ID
ax datasets export NAME_OR_ID --all
ax datasets export NAME_OR_ID --version-id VERSION_ID
More from awesome-copilot
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About this skill
What does the arize-dataset skill do?

Creates, manages, and queries Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI. Use when the user needs test data, evaluation examples, or mentions create dataset, list datasets, export dataset, append examples, dataset version, golden dataset, or test set.

How do I install it?

Run `npx skills add github/awesome-copilot --skill arize-dataset --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From github/awesome-copilot, a repository with 37,432 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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