From skills
Create and manage evaluation datasets in Adaline. Use when building test cases, adding dataset columns/rows, importing data, or triggering dynamic columns.
How this skill is triggered — by the user, by Claude, or both
Slash command
/skills:adaline-datasetsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Datasets are structured test cases for evaluations. Rows supply prompt inputs and optional expected values. Columns define the cell modality or dynamic generation source.
Datasets are structured test cases for evaluations. Rows supply prompt inputs and optional expected values. Columns define the cell modality or dynamic generation source.
Key terms:
static, prompt, or apiprompt or api column whose values are generated on demandSet these environment variables when credentials are available:
ADALINE_API_KEY — workspace API key from Admin > API KeysADALINE_PROJECT_ID — project IDBase URL: https://api.adaline.ai/v2
Column creation takes { "columns": [...] }. Row creation takes { "rows": [...] }. Do not send a single bare column object to /columns.
| Symptom | First Fix |
|---|---|
| Column add fails | Wrap columns in { "columns": [...] } |
| Row values not applied | Use valuesBy=columnName when keys are names |
| Dynamic fetch ignored rows | Use datasetRowIds; the shorter legacy row-id key is not accepted |
| Pagination missing rows | Use pagination.nextCursor |
| Python snippets return coroutine | Await SDK methods |
curl -X POST "https://api.adaline.ai/v2/datasets" \
-H "Authorization: Bearer $ADALINE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"projectId": "project_abc123",
"title": "Support eval set",
"icon": { "type": "emoji", "value": "📚" },
"description": "Support questions and expected answers"
}'
curl -X POST "https://api.adaline.ai/v2/datasets/dataset_abc123/columns" \
-H "Authorization: Bearer $ADALINE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"columns": [
{ "name": "question", "type": "static" },
{ "name": "expected_answer", "type": "static" },
{
"name": "draft_answer",
"type": "prompt",
"settings": { "promptId": "prompt_abc123" }
}
]
}'
API dynamic column:
{
"name": "retrieved_context",
"type": "api",
"settings": {
"method": "POST",
"url": "https://example.com/retrieve",
"headers": { "Authorization": "Bearer token" },
"bodyTemplate": "{ \"query\": \"{{question}}\" }"
}
}
curl -X POST "https://api.adaline.ai/v2/datasets/dataset_abc123/rows?valuesBy=columnName" \
-H "Authorization: Bearer $ADALINE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"rows": [
{
"values": {
"question": { "value": "How do I reset my password?" },
"expected_answer": { "value": "Send the reset link." }
}
}
]
}'
curl -X POST "https://api.adaline.ai/v2/datasets/dataset_abc123/dynamic-columns/fetch" \
-H "Authorization: Bearer $ADALINE_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"columnIds": ["column_abc123"],
"datasetRowIds": ["row_abc123"],
"runMode": "all"
}'
runMode can be all, failed, or first.
await adaline.datasets.list({ projectId, limit: 20 });
await adaline.datasets.create({ dataset });
await adaline.datasets.columns.create({ datasetId, columns });
await adaline.datasets.rows.create({ datasetId, valuesBy: 'columnName', rows });
await adaline.datasets.columns.fetchDynamic({ datasetId, query });
await adaline.datasets.list(project_id=project_id, limit=20)
await adaline.datasets.create(dataset=dataset)
await adaline.datasets.columns.create(dataset_id=dataset_id, columns=columns)
await adaline.datasets.rows.create(dataset_id=dataset_id, values_by="columnName", rows=rows)
await adaline.datasets.columns.fetch_dynamic(dataset_id=dataset_id, query=query)
valuesBy=columnName for authoring fixtures; use column IDs for immutable machine integrations.datasetRowIds to rerun dynamic generation for a focused subset.See references/api.md for the full REST contract.
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