# Arize Dataset

> INVOKE THIS SKILL when creating, managing, or querying Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI.

- Skill: `majiayu000/arize-dataset` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds add majiayu000/arize-dataset`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/arize-dataset/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/majiayu000/arize-dataset

---


# Arize Dataset Skill

## 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

Three things are needed: `ax` CLI, an API key (env var or profile), and a space ID. A project name is also needed but usually comes from the user's message.

### Install ax

If `ax` is not installed, not on PATH, or below version `0.3.0`, see ax-setup.md.

### Verify environment

Run a quick check for credentials:

**macOS/Linux (bash):**
```bash
ax --version && echo "--- env ---" && if [ -n "$ARIZE_API_KEY" ]; then echo "ARIZE_API_KEY: (set)"; else echo "ARIZE_API_KEY: (not set)"; fi && echo "ARIZE_SPACE_ID: ${ARIZE_SPACE_ID:-(not set)}" && echo "--- profiles ---" && ax profiles show 2>&1
```

**Windows (PowerShell):**
```powershell
ax --version; Write-Host "--- env ---"; Write-Host "ARIZE_API_KEY: $(if ($env:ARIZE_API_KEY) { '(set)' } else { '(not set)' })"; Write-Host "ARIZE_SPACE_ID: $env:ARIZE_SPACE_ID"; Write-Host "--- profiles ---"; ax profiles show 2>&1
```

**Read the output and proceed immediately** if either the env var or the profile has an API key. Only ask the user if **both** are missing. Resolve failures:

- No API key in env **and** no profile → **AskQuestion**: "Arize API key (https://app.arize.com/admin > API Keys)"
- Space ID unknown → run `ax spaces list -o json` to list all accessible spaces and pick the right one, or **AskQuestion** if the user prefers to provide it directly
- Project unclear → ask, or run `ax projects list -o json --limit 100` and present as selectable options

### Space ID and Project

Both are needed for most commands. Resolve each:

1. User provides it in the conversation -- use directly via `--space-id` / `--project` flags.
2. Env var is set (`ARIZE_SPACE_ID`, `ARIZE_DEFAULT_PROJECT`) -- use silently.
3. If missing, **AskQuestion** once. Tell the user:
   - Run `ax spaces list -o json` to discover your space ID, or find it in the Arize URL: `/spaces/{SPACE_ID}/...`
   - Project is the project name as shown in the Arize UI.
   - For convenience, recommend setting env vars so they don't get asked again:
     `export ARIZE_SPACE_ID="U3BhY2U6..."` and `export ARIZE_DEFAULT_PROJECT="my-project"`

Prefer asking the user over searching or iterating through projects and API keys.
If you get a `401 Unauthorized`, tell the user their API key may not have access to
that space and ask them to verify.

## List Datasets: `ax datasets list`

Browse datasets in a space. Output goes to stdout.

```bash
ax datasets list
ax datasets list --space-id SPACE_ID --limit 20
ax datasets list --cursor CURSOR_TOKEN
ax datasets list -o json
```

### Flags

| Flag | Type | Default | Description |
|------|------|---------|-------------|
| `--space-id` | string | from profile | Filter by space |
| `--limit, -l` | int | 15 | Max results (1-100) |
| `--cursor` | string | none | Pagination cursor from previous response |
| `-o, --output` | string | table | Output format: table, json, csv, parquet, or file path |
| `-p, --profile` | string | default | Configuration profile |

## Get Dataset: `ax datasets get`

Quick metadata lookup -- returns dataset name, space, timestamps, and version list.

```bash
ax datasets get DATASET_ID
ax datasets get DATASET_ID -o json
```

### Flags

| Flag | Type | Default | Description |
|------|------|---------|-------------|
| `DATASET_ID` | string | required | Positional argument |
| `-o, --output` | string | table | Output format |
| `-p, --profile` | string | default | Configuration profile |

### Response fields

| Field | Type | Description |
|-------|------|-------------|
| `id` | string | Dataset ID |
| `name` | string | Dataset name |
| `space_id` | string | Space this dataset belongs to |
| `created_at` | datetime | When the dataset was created |
| `updated_at` | datetime | Last modification time |
| `versions` | array | List of dataset versions (id, name, dataset_id, created_at, updated_at) |

## Export Dataset: `ax datasets export`

Download all examples to a file. Use `--all` for datasets larger than 500 examples (unlimited bulk export).

```bash
ax datasets export DATASET_ID
# -> dataset_abc123_20260305_141500/examples.json

ax datasets export DATASET_ID --all
ax datasets export DATASET_ID --version-id VERSION_ID
ax datasets export DATASET_ID --output-dir ./data
ax datasets export DATASET_ID --stdout
ax datasets export DATASET_ID --stdout | jq '.[0]'
```

### Flags

| Flag | Type | Default | Description |
|------|------|---------|-------------|
| `DATASET_ID` | string | required | Positional argument |
| `--version-id` | string | latest | Export a specific dataset version |
| `--all` | bool | false | Unlimited bulk export (use for datasets > 500 examples) |
| `--output-dir` | string | `.` | Output directory |
| `--stdout` | bool | false | Print JSON to stdout instead of file |
| `-p, --profile` | string | default | Configuration profile |

**Agent auto-escalation rule:** If an export returns exactly 500 examples, the result is likely truncated — re-run with `--all` to get the full dataset.

**Export completeness verification:** After exporting, confirm the row count matches what the server reports:
```bash
# Get the server-reported count from dataset metadata
ax datasets get DATASET_ID -o json | jq '.versions[-1] | {version: .id, examples: .example_count}'

# Compare to what was exported
jq 'length' dataset_*/examples.json

# If counts differ, re-export with --all
```

Output is a JSON array of example objects. Each example has system fields (`id`, `created_at`, `updated_at`) plus all user-defined fields:

```json
[
  {
    "id": "ex_001",
    "created_at": "2026-01-15T10:00:00Z",
    "updated_at": "2026-01-15T10:00:00Z",
    "question": "What is 2+2?",
    "answer": "4",
    "topic": "math"
  }
]
```

## Create Dataset: `ax datasets create`

Create a new dataset from a data file.

```bash
ax datasets create --name "My Dataset" --space-id SPACE_ID --file data.csv
ax datasets create --name "My Dataset" --space-id SPACE_ID --file data.json
ax datasets create --name "My Dataset" --space-id SPACE_ID --file data.jsonl
ax datasets create --name "My Dataset" --space-id SPACE_ID --file data.parquet
```

### Flags

| Flag | Type | Required | Description |
|------|------|----------|-------------|
| `--name, -n` | string | yes | Dataset name |
| `--space-id` | string | yes | Space to create the dataset in |
| `--file, -f` | path | yes | Data file: CSV, JSON, JSONL, or Parquet |
| `-o, --output` | string | no | Output format for the returned dataset metadata |
| `-p, --profile` | string | no | Configuration profile |

### Supported file formats

| Format | Extension | Notes |
|--------|-----------|-------|
| CSV | `.csv` | Column headers become field names |
| JSON | `.json` | Array of objects |
| JSON Lines | `.jsonl` | One object per line (NOT a JSON array) |
| Parquet | `.parquet` | Column names become field names; preserves types |

**Format gotchas:**
- **CSV**: Loses type information — dates become strings, `null` becomes empty string. Use JSON/Parquet to preserve types.
- **JSONL**: Each line is a separate JSON object. A JSON array (`[{...}, {...}]`) in a `.jsonl` file will fail — use `.json` extension instead.
- **Parquet**: Preserves column types. Requires `pandas`/`pyarrow` to read locally: `pd.read_parquet("examples.parquet")`.

## Append Examples: `ax datasets append`

Add examples to an existing dataset. Two input modes -- use whichever fits.

### Inline JSON (agent-friendly)

Generate the payload directly -- no temp files needed:

```bash
ax datasets append DATASET_ID --json '[{"question": "What is 2+2?", "answer": "4"}]'

ax datasets append DATASET_ID --json '[
  {"question": "What is gravity?", "answer": "A fundamental force..."},
  {"question": "What is light?", "answer": "Electromagnetic radiation..."}
]'
```

### From a file

```bash
ax datasets append DATASET_ID --file new_examples.csv
ax datasets append DATASET_ID --file additions.json
```

### To a specific version

```bash
ax datasets append DATASET_ID --json '[{"q": "..."}]' --version-id VERSION_ID
```

### Flags

| Flag | Type | Required | Description |
|------|------|----------|-------------|
| `DATASET_ID` | string | yes | Positional argument |
| `--json` | string | mutex | JSON array of example objects |
| `--file, -f` | path | mutex | Data file (CSV, JSON, JSONL, Parquet) |
| `--version-id` | string | no | Append to a specific version (default: latest) |
| `-o, --output` | string | no | Output format for the returned dataset metadata |
| `-p, --profile` | string | no | Configuration profile |

Exactly one of `--json` or `--file` is required.

### Validation

- Each example must be a JSON object with at least one user-defined field
- Maximum 100,000 examples per request

**Schema validation before append:** If the dataset already has examples, inspect its schema before appending to avoid silent field mismatches:

```bash
# Check existing field names in the dataset
ax datasets export DATASET_ID --stdout | jq '.[0] | keys'

# Verify your new data has matching field names
echo '[{"question": "..."}]' | jq '.[0] | keys'

# Both outputs should show the same user-defined fields
```

Fields are free-form: extra fields in new examples are added, and missing fields become null. However, typos in field names (e.g., `queston` vs `question`) create new columns silently -- verify spelling before appending.

## Delete Dataset: `ax datasets delete`

```bash
ax datasets delete DATASET_ID
ax datasets delete DATASET_ID --force   # skip confirmation prompt
```

### Flags

| Flag | Type | Default | Description |
|------|------|---------|-------------|
| `DATASET_ID` | string | required | Positional argument |
| `--force, -f` | bool | false | Skip confirmation prompt |
| `-p, --profile` | string | default | Configuration profile |

## Workflows

### Find a dataset by name

Users often refer to datasets by name rather than ID. Resolve a name to an ID before running other commands:

```bash
# Find dataset ID by name
ax datasets list -o json | jq '.[] | select(.name == "eval-set-v1") | .id'

# If the list is paginated, fetch more
ax datasets list -o json --limit 100 | jq '.[] | select(.name | test("eval-set")) | {id, name}'
```

### Create a dataset from file for evaluation

1. Prepare a CSV/JSON/Parquet file with your evaluation columns (e.g., `input`, `expected_output`)
2. `ax datasets create --name "eval-set-v1" --space-id SPACE_ID --file eval_data.csv`
3. Verify: `ax datasets get DATASET_ID`
4. Use the dataset ID to run experiments

### Add examples to an existing dataset

```bash
# Find the dataset
ax datasets list

# Append inline or from a file (see Append Examples section for full syntax)
ax datasets append DATASET_ID --json '[{"question": "...", "answer": "..."}]'
ax datasets append DATASET_ID --file additional_examples.csv
```

### Download dataset for offline analysis

1. `ax datasets list` -- find the dataset
2. `ax datasets export DATASET_ID` -- download to file
3. Parse the JSON: `jq '.[] | .question' dataset_*/examples.json`

### Export a specific version

```bash
# List versions
ax datasets get DATASET_ID -o json | jq '.versions'

# Export that version
ax datasets export DATASET_ID --version-id VERSION_ID
```

### Iterate on a dataset

1. Export current version: `ax datasets export DATASET_ID`
2. Modify the examples locally
3. Append new rows: `ax datasets append DATASET_ID --file new_rows.csv`
4. Or create a fresh version: `ax datasets create --name "eval-set-v2" --space-id SPACE_ID --file updated_data.json`

### Pipe export to other tools

```bash
# Count examples
ax datasets export DATASET_ID --stdout | jq 'length'

# Extract a single field
ax datasets export DATASET_ID --stdout | jq '.[].question'

# Convert to CSV with jq
ax datasets export DATASET_ID --stdout | jq -r '.[] | [.question, .answer] | @csv'
```

## Dataset Example Schema

Examples are free-form JSON objects. There is no fixed schema -- columns are whatever fields you provide. System-managed fields are added by the server:

| Field | Type | Managed by | Notes |
|-------|------|-----------|-------|
| `id` | string | server | Auto-generated UUID. Required on update, forbidden on create/append |
| `created_at` | datetime | server | Immutable creation timestamp |
| `updated_at` | datetime | server | Auto-updated on modification |
| *(any user field)* | any JSON type | user | String, number, boolean, null, nested object, array |


## Related Skills

- **arize-trace**: Export production spans to understand what data to put in datasets → use `arize-trace`
- **arize-experiment**: Run evaluations against this dataset → next step is `arize-experiment`
- **arize-prompt-optimization**: Use dataset + experiment results to improve prompts → use `arize-prompt-optimization`

## Troubleshooting

| Problem | Solution |
|---------|----------|
| `ax: command not found` | See ax-setup.md |
| `401 Unauthorized` | API key may not have access to this space. Verify the key and space ID are correct. Keys are scoped per space -- get the right one from https://app.arize.com/admin > API Keys. |
| `No profile found` | Run `ax profiles show --expand` to check; set `ARIZE_API_KEY` env var or write `~/.arize/config.toml` |
| `Dataset not found` | Verify dataset ID with `ax datasets list` |
| `File format error` | Supported: CSV, JSON, JSONL, Parquet |
| `platform-managed column` | Remove `id`, `created_at`, `updated_at` from create/append payloads |
| `reserved column` | Remove `time`, `count`, or any `source_record_*` field |
| `Provide either --json or --file` | Append requires exactly one input source |
| `Examples array is empty` | Ensure your JSON array or file contains at least one example |
| `not a JSON object` | Each element in the `--json` array must be a `{...}` object, not a string or number |

## Save Credentials for Future Use

At the **end of the session**, if the user manually provided any of the following during this conversation (via AskQuestion response, pasted text, or inline values) **and** those values were NOT already loaded from a saved profile or environment variable, offer to save them for future use.

| Credential | Where it gets saved |
|------------|---------------------|
| API key | `ax` profile at `~/.arize/config.toml` |
| Space ID | **macOS/Linux:** shell config (`~/.zshrc` or `~/.bashrc`) as `export ARIZE_SPACE_ID="..."`. **Windows:** user environment variable via `[System.Environment]::SetEnvironmentVariable('ARIZE_SPACE_ID', '...', 'User')` |

**Skip this entirely if:**
- The API key was already loaded from an existing profile or `ARIZE_API_KEY` env var
- The space ID was already set via `ARIZE_SPACE_ID` env var
- The user only used base64 project IDs (no space ID was needed)

**How to offer:** Use **AskQuestion**: *"Would you like to save your Arize credentials so you don't have to enter them next time?"* with options `"Yes, save them"` / `"No thanks"`.

**If the user says yes:**

1. **API key** — Check if `~/.arize/config.toml` exists. If it does, read it and update the `[auth]` section. If not, create it with this minimal content:

   ```toml
   [profile]
   name = "default"

   [auth]
   api_key = "THE_API_KEY"

   [output]
   format = "table"
   ```

   Verify with: `ax profiles show`

2. **Space ID** — Persist the space ID as an environment variable:

   **macOS/Linux** — Detect the user's shell config file (`~/.zshrc` for zsh, `~/.bashrc` for bash). Append:

   ```bash
   export ARIZE_SPACE_ID="THE_SPACE_ID"
   ```

   Tell the user to run `source ~/.zshrc` (or restart their terminal) for it to take effect.

   **Windows (PowerShell)** — Set a persistent user environment variable:

   ```powershell
   [System.Environment]::SetEnvironmentVariable('ARIZE_SPACE_ID', 'THE_SPACE_ID', 'User')
   ```

   Tell the user to restart their terminal for it to take effect.