skills/arize-dataset/SKILL.md
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.
npx skillsauth add arize-ai/arize-skills arize-datasetInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SPACE— All--spaceflags and theARIZE_SPACEenv var accept a space name (e.g.,my-workspace) or a base64 space ID (e.g.,U3BhY2U6...). Find yours withax spaces list.
question, answer, context)System-managed fields on examples (id, created_at, updated_at) are auto-generated by the server -- never include them in create or append payloads.
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.md401 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 references/ax-profiles.md to create/update it. If the user doesn't have their key, direct them to https://app.arize.com/admin > API Keysax spaces list to pick by name, or ask the userax projects list -o json --limit 100 and present as selectable options.env files or search the filesystem for credentials. Use ax profiles for Arize credentials and ax ai-integrations for LLM provider keys. If credentials are not available through these channels, ask the user.ax datasets listBrowse datasets in a space. Output goes to stdout.
ax datasets list
ax datasets list --space SPACE --limit 20
ax datasets list --cursor CURSOR_TOKEN
ax datasets list -o json
| Flag | Type | Default | Description |
|------|------|---------|-------------|
| --space | string | from profile | Filter by space |
| --name, -n | string | none | Substring filter on dataset name |
| --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 |
ax datasets getQuick metadata lookup -- returns dataset name, space, timestamps, and version list.
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
| Flag | Type | Default | Description |
|------|------|---------|-------------|
| NAME_OR_ID | string | required | Dataset name or ID (positional) |
| --space | string | none | Space name or ID (required if using dataset name instead of ID) |
| -o, --output | string | table | Output format |
| 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) |
ax datasets exportDownload all examples to a file. Use --all for datasets larger than 500 examples (unlimited bulk export).
ax datasets export NAME_OR_ID
# -> dataset_abc123_20260305_141500/examples.json
ax datasets export NAME_OR_ID --all
ax datasets export NAME_OR_ID --version-id VERSION_ID
ax datasets export NAME_OR_ID --output-dir ./data
ax datasets export NAME_OR_ID --stdout
ax datasets export NAME_OR_ID --stdout | jq '.[0]'
ax datasets export NAME_OR_ID --space SPACE # required when using dataset name instead of ID
| Flag | Type | Default | Description |
|------|------|---------|-------------|
| NAME_OR_ID | string | required | Dataset name or ID (positional) |
| --space | string | none | Space name or ID (required if using dataset name instead of ID) |
| --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 |
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:
# Get the server-reported count from dataset metadata
ax datasets get DATASET_NAME --space SPACE -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:
[
{
"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"
}
]
ax datasets createCreate a new dataset from a data file.
ax datasets create --name "My Dataset" --space SPACE --file data.csv
ax datasets create --name "My Dataset" --space SPACE --file data.json
ax datasets create --name "My Dataset" --space SPACE --file data.jsonl
ax datasets create --name "My Dataset" --space SPACE --file data.parquet
| Flag | Type | Required | Description |
|------|------|----------|-------------|
| --name, -n | string | yes | Dataset name |
| --space | 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 |
Use --file - to pipe data directly — no temp file needed:
echo '[{"question": "What is 2+2?", "answer": "4"}]' | ax datasets create --name "my-dataset" --space SPACE --file -
# Or with a heredoc
ax datasets create --name "my-dataset" --space SPACE --file - << 'EOF'
[{"question": "What is 2+2?", "answer": "4"}]
EOF
To add rows to an existing dataset, use ax datasets append --json '[...]' instead — no file needed.
| 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:
null becomes empty string. Use JSON/Parquet to preserve types.[{...}, {...}]) in a .jsonl file will fail — use .json extension instead.pandas/pyarrow to read locally: pd.read_parquet("examples.parquet").ax datasets appendAdd examples to an existing dataset. Two input modes -- use whichever fits.
Generate the payload directly -- no temp files needed:
ax datasets append DATASET_NAME --space SPACE --json '[{"question": "What is 2+2?", "answer": "4"}]'
ax datasets append DATASET_NAME --space SPACE --json '[
{"question": "What is gravity?", "answer": "A fundamental force..."},
{"question": "What is light?", "answer": "Electromagnetic radiation..."}
]'
ax datasets append DATASET_NAME --space SPACE --file new_examples.csv
ax datasets append DATASET_NAME --space SPACE --file additions.json
ax datasets append DATASET_NAME --space SPACE --json '[{"q": "..."}]' --version-id VERSION_ID
| Flag | Type | Required | Description |
|------|------|----------|-------------|
| NAME_OR_ID | string | yes | Dataset name or ID (positional); add --space when using name |
| --space | string | no | Space name or ID (required if using dataset name instead of ID) |
| --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 |
Exactly one of --json or --file is required.
Schema validation before append: If the dataset already has examples, inspect its schema before appending to avoid silent field mismatches:
# Check existing field names in the dataset
ax datasets export DATASET_NAME --space SPACE --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.
ax datasets deleteax datasets delete NAME_OR_ID
ax datasets delete NAME_OR_ID --space SPACE # required when using dataset name instead of ID
ax datasets delete NAME_OR_ID --force # skip confirmation prompt
| Flag | Type | Default | Description |
|------|------|---------|-------------|
| NAME_OR_ID | string | required | Dataset name or ID (positional) |
| --space | string | none | Space name or ID (required if using dataset name instead of ID) |
| --force, -f | bool | false | Skip confirmation prompt |
ax datasets updateRename an existing dataset.
ax datasets update NAME_OR_ID --name "new-dataset-name"
ax datasets update NAME_OR_ID --name "new-dataset-name" --space SPACE
| Flag | Type | Required | Description |
|------|------|----------|-------------|
| NAME_OR_ID | string | yes | Dataset name or ID (positional) |
| --name | string | yes | New dataset name |
| --space | string | no | Space name or ID (required if using dataset name instead of ID) |
ax datasets annotate-examplesWrite annotations onto dataset examples in bulk from a file. Upsert semantics — existing annotations with the same key are updated, new ones are created. Up to 1000 annotations per request.
ax datasets annotate-examples NAME_OR_ID --file annotations.json
ax datasets annotate-examples NAME_OR_ID --file annotations.csv --space SPACE
| Flag | Type | Required | Description |
|------|------|----------|-------------|
| NAME_OR_ID | string | yes | Dataset name or ID (positional) |
| --file, -f | path | yes | Annotation file: JSON, JSONL, CSV, or Parquet (use - for stdin) |
| --space | string | no | Space name or ID (required if using dataset name instead of ID) |
All dataset commands accept a name or ID directly. You can pass a dataset name as the positional argument (add --space SPACE when not using an ID):
# Use name directly
ax datasets get "eval-set-v1" --space SPACE
ax datasets export "eval-set-v1" --space SPACE
# Or resolve name to ID via list if you need the base64 ID
ax datasets list -o json | jq '.[] | select(.name == "eval-set-v1") | .id'
input, expected_output)
--file - (see the Create Dataset section)ax datasets create --name "eval-set-v1" --space SPACE --file eval_data.csvax datasets get DATASET_NAME --space SPACE# Find the dataset
ax datasets list --space SPACE
# Append inline or from a file using the dataset name (see Append Examples section for full syntax)
ax datasets append DATASET_NAME --space SPACE --json '[{"question": "...", "answer": "..."}]'
ax datasets append DATASET_NAME --space SPACE --file additional_examples.csv
ax datasets list --space SPACE -- find the dataset nameax datasets export DATASET_NAME --space SPACE -- download to filejq '.[] | .question' dataset_*/examples.json# List versions
ax datasets get DATASET_NAME --space SPACE -o json | jq '.versions'
# Export that version
ax datasets export DATASET_NAME --space SPACE --version-id VERSION_ID
ax datasets export DATASET_NAME --space SPACEax datasets append DATASET_NAME --space SPACE --file new_rows.csvax datasets create --name "eval-set-v2" --space SPACE --file updated_data.json# Count examples
ax datasets export DATASET_NAME --space SPACE --stdout | jq 'length'
# Extract a single field
ax datasets export DATASET_NAME --space SPACE --stdout | jq '.[].question'
# Convert to CSV with jq
ax datasets export DATASET_NAME --space SPACE --stdout | jq -r '.[] | [.question, .answer] | @csv'
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 |
arize-tracearize-experimentarize-prompt-optimization| Problem | Solution |
|---------|----------|
| ax: command not found | See references/ax-setup.md |
| 401 Unauthorized | API key is wrong, expired, or doesn't have access to this space. Fix the profile using references/ax-profiles.md. |
| No profile found | No profile is configured. See references/ax-profiles.md to create one. |
| Dataset not found | Verify dataset ID with ax datasets list |
| File format error | Supported: CSV, JSON, JSONL, Parquet. Use --file - to read from stdin. |
| 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 |
See references/ax-profiles.md § Save Credentials for Future Use.
data-ai
INVOKE THIS SKILL for Arize Prompt Hub and `ax prompts` workflows: author or import templates and save (Workflows A–B), label/promote (C), or list/get/edit/delete/duplicate (D). Use when the user mentions ax prompts, Prompt Hub, creating/editing/saving a prompt, `{variable}` placeholders, or production/staging labels. For improving prompt text using traces or eval scores, use arize-prompt-optimization. For running experiments, use arize-experiment.
tools
Manages Arize users, organizations, spaces, projects, roles, role bindings, resource restrictions, and API keys via the ax CLI. Use for enterprise admin workflows: inviting and offboarding users, onboarding new teams, creating custom roles for SAML/SSO mappings, assigning roles to users, restricting project-level access, and managing service keys for multi-tenant architectures. Covers ax users, ax organizations, ax spaces, ax projects, ax roles, ax role-bindings, and ax api-keys.
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Downloads, exports, and inspects existing Arize traces and spans to understand what an LLM app is doing or debug runtime issues. Covers exporting traces by ID, spans by ID, sessions by ID, and root-cause investigation using the ax CLI. Use when the user wants to look at existing trace data, see what their LLM app is doing, export traces, download spans, investigate errors, or analyze behavior regressions.
tools
Optimizes, improves, and debugs LLM prompts using production trace data, evaluations, and annotations. Extracts prompts from spans, gathers performance signal, and runs a data-driven optimization loop using the ax CLI. Use when the user mentions optimize prompt, improve prompt, make AI respond better, improve output quality, prompt engineering, prompt tuning, or system prompt improvement.