grill-me-intent-curator

Build grill-me-intents dataset rows from run packets and schemas.

92|6|Updated Mar 27, 2026
One-click install
npx skills add https://github.com/JayFarei/opentraces --skill grill-me-intent-curator
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: grill-me-intent-curator
Source: https://github.com/JayFarei/opentraces/tree/main/skill/workflow-authoring/examples/grill-me-intent-curator
Command: npx skills add https://github.com/JayFarei/opentraces --skill grill-me-intent-curator

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires ot trace query, ot trace map, ot trace get, and includes scripts (resource) components.

What problem does it solve?

This Skill automates the process of building rows for the grill-me-intents dataset, saving time and streamlining the workflow.

Core Features & Use Cases

  • Row Construction: Build dataset rows from run packets and schemas.
  • Candidate Identification: Utilize trace query to find candidates.
  • Output Compliance: Emit rows matching the dataset schema directly to the output.

Quick Start

To get started, invoke the skill with the run packet and schema, and let it construct rows for the dataset.

Frequently Asked Questions about grill-me-intent-curator

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

FAQPage Schema
How do I automate row construction for an intent dataset?

To automate row construction for an intent dataset, this Skill uses run packets and schemas to identify candidates via trace queries and emit compliant rows directly to the output.

What is the process for curating intent datasets from trace analysis?

Curating intent datasets from trace analysis involves querying OpenTelemetry traces to find candidate data, mapping the results, and constructing rows that strictly adhere to your target dataset schema.

Do I need OpenTelemetry trace query capabilities to build dataset rows?

Yes, you need OpenTelemetry trace query, trace map, and trace get capabilities to identify and extract the candidate data required to build rows for the intent dataset.

How do I ensure my output rows match the dataset schema correctly?

To ensure output rows match the dataset schema, the Skill automatically validates and emits candidate rows constructed from run packets, enforcing strict compliance with the predefined schema structure.

What's the best way to streamline data processing for intent dataset curation?

The best way to streamline data processing for intent dataset curation is automating candidate identification and row construction from run packets, eliminating manual trace mapping and schema validation.