Sample Rows

Overview

When you send JSON rows or a CSV file reference, we return a deterministic sample using first, last, systematic, content-hash, seeded-random, or stratified methods. The same seed and input always yield the same rows — we never use runtime randomness. Do not use this for statistically rigorous survey sampling.

Reproducible sampling is essential for debugging and audits — you need the same rows every time, not a different draw on each call.

When to use it

Scope

Non-goals

• Does not use runtime randomness
• Does not modify the source dataset
• Does not guarantee statistical representativeness

Properties

Capabilities

Cost & billing

Flat rate per invocation

File handling

File limits

Constraints this skill applies to your input and generated files. The “Limited by” column shows the static source of each cap; none of these can be raised by upgrading your plan.

How we handle your data

Input schema

Output schema

API contract

curl -sS -X POST "$BASE/v1/execute" -H "Authorization: Bearer $KEY" -H 'Content-Type: application/json' -d '{"skillKey":"data.sample_rows","input":{"rows":[{"id":1,"name":"Alice"}],"sampleSize":1,"method":"first"}}'

import { Squillify } from "@squillify/sdk";

const sq = new Squillify({ apiKey: process.env.SQUILLIFY_API_KEY });

const { output } = await sq.execute("data.sample_rows", {"rows":[{"id":1,"name":"Alice"}],"sampleSize":1,"method":"first"});

Errors

Other limits

Limitations

• Does not use runtime randomness
• Does not modify the source dataset
• Does not guarantee statistical representativeness
• Statistically rigorous survey sampling
• Unbounded streaming samples

How to call

POST /v1/execute (requires authentication)

{
  "skillKey": "data.sample_rows",
  "input": {
    "rows": [
      {
        "id": 1,
        "name": "Alice"
      }
    ],
    "sampleSize": 1,
    "method": "first"
  }
}

Examples

{
  "rows": [
    {
      "id": 1,
      "name": "Alice"
    }
  ],
  "sampleSize": 1,
  "method": "first"
}

{
  "method": "first",
  "sample": [
    {
      "name": "Alice",
      "_rowNumber": 1,
      "id": 1
    }
  ],
  "seed": "squillify",
  "sampleRowCount": 1,
  "inputRowCount": 1
}

{
  "seed": "audit-2026",
  "rows": [
    {
      "id": 1
    },
    {
      "id": 2
    },
    {
      "id": 3
    }
  ],
  "method": "hash",
  "sampleSize": 2
}

{
  "method": "hash",
  "sample": [
    {
      "id": 1,
      "_rowNumber": 1
    },
    {
      "id": 2,
      "_rowNumber": 2
    }
  ],
  "seed": "audit-2026",
  "sampleRowCount": 2,
  "inputRowCount": 3
}

Recommended use cases

• Debugging with a fixed subset
• Audit trails with seeded selection
• Preview a dataset before heavier processing

Avoid for

• Statistically rigorous survey sampling
• Unbounded streaming samples

Related skills

Composable with

Safety & privacy

• Runs without calling any external service.
• Your payloads are never stored permanently.
• Telemetry captures metadata only — never your payload contents.
• We never train models on your payloads.
• No human reviews your payloads.

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