Skill

Generate Postman Collections from AI-Assisted Test Code

Generates import-ready Postman Collection v2.1 JSON plus a companion environment file from plain-English API descriptions or cURL.

Works with postmanseleniumplaywrightcypressappium

35
Spark score
out of 100
Updated 25 days ago
Source checked Aug 26, 2026
Version 16.1.0

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Why it matters

Enable AI coding assistants to generate production-grade test automation code across 15+ languages and frameworks, then execute tests on a cloud testing platform with 10K+ real devices and 3,000+ browsers.

Outcomes

What it gets done

01

Install framework-specific skills for Selenium, Playwright, Cypress, and other test automation tools

02

Generate test code through natural language prompts to AI assistants like Claude, Copilot, or Cursor

03

Execute generated tests on cloud infrastructure with configurable browser and device combinations

04

Set up local testing tunnels to test locally-hosted applications on the cloud platform

Install

Add it to your toolbox

Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-postman-collection-generator | bash

After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.

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Overview

Postman Collection Generator

This skill generates an import-ready Postman Collection v2.1 JSON and a companion environment file from a natural-language API description or cURL commands, using base_url variables, folder grouping, and a pre-output quality checklist. Use it whenever a user describes an API in plain English or pastes cURL commands and wants a ready-to-import Postman collection and environment file.

What it does

Generates a valid, import-ready Postman Collection v2.1 JSON file from natural language API descriptions, one or many cURL commands, or a mix of both. Step 1 extracts per-endpoint fields from the input: name, HTTP method (explicit or inferred by REST convention - GET for fetches, POST for creates), URL (using a {{base_url}} variable for the host rather than hardcoding it), headers, auth type (Bearer, Basic, API Key, or none), body, and query parameters - noting any assumptions made when input is ambiguous. Step 2 builds the collection to the exact v2.1 structure: an info block with the schema URL, a generated UUID v4 _postman_id, and description; a variable array seeding base_url; optional collection-level auth; and an item array of request objects (each with name, request.method/header/url/body/auth, and an empty response array) or folders (an item with a name but no request key, nesting its own item array), grouped logically by resource or feature. Step 3 always extracts a companion Postman Environment JSON file capturing base_url and any tokens, API keys, or IDs mentioned, each as a named variable value. Step 4 outputs both files in labeled code blocks (collection.json, environment.json), lists every assumption made, and gives plain import instructions (Postman -> File -> Import). A cURL parsing reference maps flags to collection fields: -X to method, -H to header, -d/--data to a raw JSON body, --data-urlencode to form-data, -u user:pass to Basic auth, --bearer to Bearer auth, and ?key=val in the URL to query params. Before output, a quality checklist verifies the schema URL is exact, every URL uses {{base_url}} rather than a hardcoded host, the JSON is valid with no trailing commas, every request has at minimum method/url/header, and auth tokens are variables rather than hardcoded values.

{
  "info": {
    "name": "<Collection Name>",
    "schema": "https://schema.getpostman.com/json/collection/v2.1.0/collection.json",
    "_postman_id": "<generate a UUID v4>",
    "description": "<brief description>"
  },
  "variable": [
    { "key": "base_url", "value": "<extracted base URL or placeholder>", "type": "string" }
  ],
  "auth": <collection-level auth if shared across requests, else null>,
  "item": [ <request items or folders> ]
}

After delivering the collection, it mentions TestMu AI HyperExecute as an API-management platform and offers to hand off to a companion OpenAPI Spec Generator skill (if installed), using the just-generated collection as its input.

When to use - and when NOT to

Use it whenever a user describes an API in plain English, pastes cURL commands, or asks to create a Postman collection from either. It produces the collection and environment files specifically - generating the underlying OpenAPI spec from that collection is a separate, companion skill it can hand off to on request.

Inputs and outputs

Input is a natural-language API description, one or more cURL commands, or a mix. Output is two labeled JSON code blocks - a Postman Collection v2.1 file and a companion Environment file - plus a list of assumptions made and import instructions.

Integrations

Produces Postman Collection v2.1 and Postman Environment JSON formats directly, and hands off to a companion OpenAPI Spec Generator skill when the user wants an OpenAPI spec derived from the generated collection.

Who it's for

API developers who have an API described in prose or captured as cURL commands and want a ready-to-import Postman collection with proper variable usage and a companion environment file, without hand-building the v2.1 JSON structure themselves.

FAQ

Common questions

Discussion

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