How does it sequence tasks during a breakdown?

It prioritizes infrastructure and configuration first, followed by core logic changes, then dependent files and integrations, and finally verification steps.

Which ticketing systems are supported?

The skill is platform-agnostic and works with content pasted from Jira, GitHub Issues, Azure DevOps, Linear, and any other system that provides work item descriptions.

What is the recommended task granularity?

The skill follows a rule where one task represents one logical change that can be committed independently, typically representing 5 to 30 minutes of development work.

How does this skill save tokens?

It uses file path compression via glob patterns, removes redundant or implicit acceptance criteria, and applies terse language rules to minimize character count without losing critical context.

Can it help me write better tickets?

Yes, it includes completeness criteria that analyze titles, descriptions, and acceptance criteria to ensure they provide enough context and 'Definition of Done' for a developer to start work.

Work Items Optimizer

Name: Work Items Optimizer
Author: dariuszparys

bydariuszparys

生产力与工作流

Optimizes and breaks down software development tickets into token-efficient, actionable tasks for LLM-assisted workflows.

关于

The Work Items skill streamlines the bridge between project management tools and AI-driven development by transforming complex tickets from platforms like Jira, GitHub, or Azure DevOps into structured, LLM-optimized formats. It uses advanced patterns like file path compression and terse language to save context window space while ensuring requirements are clear, testable, and logically sequenced. This skill helps developers validate ticket completeness and automatically break down large features into granular, independent tasks ready for immediate implementation.

主要功能

Token-efficient work item formatting with glob pattern file path compression
Completeness analysis for titles, descriptions, and testable requirements
0 GitHub stars
Platform-agnostic support for Jira, GitHub, Azure DevOps, and Linear
Automated task breakdown with logical sequencing and independent commit points
Intelligent filtering of redundant or implicit acceptance criteria

使用场景

Validating if a newly created ticket contains sufficient context and testable criteria for implementation
Reducing the token footprint of a complex GitHub issue to fit within the LLM context window
Converting a broad Jira epic into a series of actionable, granular development tasks

关于

主要功能

Token-efficient work item formatting with glob pattern file path compression
Completeness analysis for titles, descriptions, and testable requirements
0 GitHub stars
Platform-agnostic support for Jira, GitHub, Azure DevOps, and Linear
Automated task breakdown with logical sequencing and independent commit points
Intelligent filtering of redundant or implicit acceptance criteria

使用场景

Validating if a newly created ticket contains sufficient context and testable criteria for implementation
Reducing the token footprint of a complex GitHub issue to fit within the LLM context window
Converting a broad Jira epic into a series of actionable, granular development tasks