add-indicator

Add technical indicators to a Go project using generics and streaming data workflows.

1.2k|199|Updated Jun 11, 2021
One-click install
npx skills add https://github.com/cinar/indicator --skill add-indicator
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: add-indicator
Source: https://github.com/cinar/indicator/tree/main/.gemini/skills/add-indicator
Command: npx skills add https://github.com/cinar/indicator --skill add-indicator

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Introduces a standardized, end-to-end workflow for adding new technical indicators to the indicator project, ensuring consistency with streaming data patterns, Go generics, and a channel-based architecture.

Core Features & Use Cases

  • Enforces a category-based organization (trend, momentum, volatility, volume, valuation) and a reusable indicator scaffold.
  • Guides implementation details: streaming inputs/outputs with generics, factory constructors, and a predictable Compute/IdlePeriod interface.
  • Supports testing and documentation practices to simplify integration of new indicators like SMA, EMA, RSI, and others.

Quick Start

Follow the workflow to implement a new indicator by selecting a category, coding with generics for a streaming pipeline, and adding tests.

Frequently Asked Questions about add-indicator

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

FAQPage Schema
How do I add a new technical indicator to a Go project using streaming data?▼

To add a new technical indicator, you follow a workflow that uses Go generics for streaming data pipelines, selects the appropriate category like trend or momentum, and implements a channel-based factory constructor with Compute and IdlePeriod interfaces.

What is the standard structure for implementing indicators like SMA or RSI in Go?▼

The standard structure for indicators like SMA or RSI involves a category-based organization, frontmatter documentation, a generics-based streaming input and output pipeline, and predictable testing standards to ensure consistent integration.

Can I use Go generics to build a channel-based architecture for EMA calculations?▼

Yes, you can use Go generics to build a channel-based architecture for EMA calculations, utilizing factory constructors and a standardized streaming data workflow to process continuous inputs efficiently.

What's the best way to organize technical indicators across different categories?▼

The best way to organize technical indicators is by mapping them to specific categories such as trend, momentum, volatility, volume, and valuation, ensuring a reusable scaffold and consistent coding standards across the project.

How does the Compute and IdlePeriod interface work for streaming indicators?▼

The Compute and IdlePeriod interface provides a predictable execution flow for streaming indicators, processing continuous channel-based inputs and managing warm-up periods before generating valid indicator outputs.

What testing standards should I follow when creating a new momentum indicator?▼

When creating a new momentum indicator, you should follow standardized testing practices that validate the channel-based streaming outputs against expected values, simplifying the integration of new indicators into the existing project architecture.