kql-and-indexing

Explain Kinetic Query Language operators and indexing for Platform submissions.

Updated Feb 24, 2026
One-click install
npx skills add https://github.com/kineticdata/kinetic-platform-ai-skills --skill kql-and-indexing
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: kql-and-indexing
Source: https://github.com/kineticdata/kinetic-platform-ai-skills/tree/main/skills/platform/kql-and-indexing
Command: npx skills add https://github.com/kineticdata/kinetic-platform-ai-skills --skill kql-and-indexing

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you efficiently search and retrieve data within the Kinetic Platform by explaining Kinetic Query Language (KQL) and the critical role of form and kapp-level indexing.

Core Features & Use Cases

  • KQL Syntax: Understand operators like =, IN, =*, !=, and OR.
  • Indexing: Learn how to define and build form-level and kapp-level indexes for faster queries.
  • Query Optimization: Discover best practices to avoid common pitfalls and ensure your queries return accurate results.
  • Use Case: You need to find all 'Open' hardware requests assigned to a specific user. This Skill guides you on how to construct the correct KQL query and ensure the necessary indexes are in place for performance.

Quick Start

Use the kql-and-indexing skill to learn how to query submissions using the 'IN' operator and ensure the 'values[Status]' field is indexed.

Frequently Asked Questions about kql-and-indexing

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I query Kinetic Platform submissions using KQL operators?

Query Kinetic Platform submissions using KQL operators like equality (=), IN, and OR to filter data. You construct query strings targeting specific submission fields to retrieve matching records efficiently through the API.

What is the difference between form-level and kapp-level indexes in Kinetic Platform?

Form-level indexes optimize queries targeting a single form's submissions, while kapp-level indexes support broader searches across an entire kapp. Both compound and single-field indexes accelerate KQL data retrieval performance.

How do I build a compound index for Kinetic Query Language searches?

Build a compound index in Kinetic Query Language by defining multiple fields within your form or kapp index definition. This allows range and equality operators to query combined fields efficiently without client-side filtering.

Why does my KQL query return inaccurate results or fail?

KQL queries return inaccurate results due to common gotchas like missing form indexes or incorrect operator syntax. Ensure queried fields are properly indexed and validate operators like IN and range filters against Kinetic Platform API requirements.

Can I use client-side filtering strategies for Kinetic Platform data retrieval?

Client-side filtering strategies work for Kinetic Platform data retrieval when server-side KQL indexing is unavailable. However, relying on API range operators and indexed fields yields faster, more accurate submission query results.

Do I need to understand the Kinetic Platform API to use KQL effectively?

Understanding the Kinetic Platform API is required to implement KQL effectively. You must know how to pass KQL query strings, define form index structures, and handle API responses for successful submission data retrieval.