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issues-to-tasks

Break down issue descriptions into ordered, typed AI-executable tasks.

1|Updated Apr 13, 2026
Search Tags:#issue#developer-workflow#task-decomposition#task-planning#ticket-triage#ai-executable-tasks
One-click install
npx skills add https://github.com/avoidthekitchen/avilingo-v2 --skill issues-to-tasks
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: issues-to-tasks
Source: https://github.com/avoidthekitchen/avilingo-v2/tree/main/.agents/skills/issues-to-tasks
Command: npx skills add https://github.com/avoidthekitchen/avilingo-v2 --skill issues-to-tasks

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Many issue tracker entries are high-level, ambiguous, or too large for a single development session. This Skill converts a single vertical-slice issue into a clear, ordered list of focused tasks that an AI or developer can execute one at a time, reducing onboarding friction and making implementation predictable.

Core Features & Use Cases

  • Locate & contextualize: Instructs how to retrieve the issue, find the parent PRD, and identify the code areas to touch.
  • Codebase exploration guidance: Highlights files, patterns, and interfaces to respect when implementing the issue.
  • Task drafting and ordering: Produces numbered tasks labeled by type (WRITE, TEST, MIGRATE, CONFIG, REVIEW), each with a verifiable output and dependency links.
  • User validation step: Prompts a short review cycle to confirm task size and ordering, then saves an approved task file in the requested template and location.
  • Use cases: Preparing a ticket for an AI coding session, triaging a backlog item for a sprint, or splitting a feature into reviewer-friendly pull request sized pieces.

Quick Start

Break down issue 123 into an ordered list of AI-executable tasks, labeling each task with type, expected output, and dependency numbers.

Frequently Asked Questions about issues-to-tasks

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

FAQPage Schema
How do I break down a single issue into AI-executable tasks?▼

To break down a single issue into AI-executable tasks, the skill parses the issue description and generates a numbered, ordered list of typed tasks (WRITE, TEST, MIGRATE, CONFIG, REVIEW) with verifiable outputs and dependency links. It then saves an approved task-file template for single-session AI execution.

What is the best way to prepare a vertical-slice ticket for an AI coding session?▼

The best way to prepare a vertical-slice ticket for an AI coding session is to decompose it into focused, ordered tasks. This process contextualizes the parent PRD, highlights relevant code patterns, and produces a storable task file suitable for AI agents.

How does task decomposition handle dependency ordering for development tickets?▼

Task decomposition handles dependency ordering by analyzing the issue requirements and labeling each task with specific dependency numbers. This ensures developers and AI agents execute tasks in the correct sequence, making implementation predictable and reducing onboarding friction.

Can I use this task planning approach to triage backlog items for a sprint?▼

Yes, you can use this task planning approach to triage backlog items for a sprint. It converts high-level or ambiguous issue tracker entries into reviewer-friendly, pull request sized pieces with clear outputs, making sprint triage and implementation predictable.

Does the generated task file template support codebase exploration guidance?▼

Yes, the generated task file template supports codebase exploration guidance. The skill highlights specific files, patterns, and interfaces to respect when implementing the issue, ensuring the AI agent or developer touches the correct code areas during execution.

When should I not use automated ticket triage for splitting features?▼

You should not use automated ticket triage if your issue lacks a clear description or parent PRD context. The skill requires a defined vertical-slice issue to accurately identify code areas, validate task ordering, and produce verifiable outputs for AI execution.

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