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TaylorHuston
TaylorHustonCOMMUNITY
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issue

Creates TASK, SPIKE, or BUG work items from natural-language conversations with AI-driven type detection.

69|7|Updated Jan 19, 2026
Search Tags:#workflow#nlp#task-management#issue-tracking#ai-assisted#spec-integration
One-click install
npx skills add https://github.com/TaylorHuston/local-life-manager --skill issue-taylorhuston
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: issue
Source: https://github.com/TaylorHuston/local-life-manager/tree/main/.claude/skills/issue
Command: npx skills add https://github.com/TaylorHuston/local-life-manager --skill issue-taylorhuston

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps teams and individuals quickly create and categorize work items (TASK, SPIKE, or BUG) with AI-driven type detection, ensuring nothing gets lost in scattered notes.

Core Features & Use Cases

  • AI-assisted type detection to create standalone work items from natural conversations.
  • Supports TASK, SPIKE, and BUG with consistent file structure and status tracking.
  • Enables integration with specs and planning artifacts to streamline project workflows.

Quick Start

/issue /issue "Implement authentication" // AI detects: TASK /issue "Compare GraphQL vs REST" // AI detects: SPIKE /issue "Broken link in project-brief" // AI detects: BUG /issue --project coordinatr

Frequently Asked Questions about issue

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

FAQPage Schema
How do I create work items from natural language conversations?▼

To create work items from natural language, you provide a text description and the AI automatically detects whether it is a TASK, SPIKE, or BUG, generating a standalone structured file with status tracking.

Can I use natural language to track bugs versus tasks in my project workflow?▼

Yes, AI-assisted type detection automatically categorizes natural language inputs into BUGs or TASKs, applying consistent file structures and status tracking to streamline project issue-tracking workflows.

How does AI-assisted type detection work for issue tracking?▼

AI-assisted type detection works by analyzing natural conversation text and categorizing it as a TASK, SPIKE, or BUG, then converting that input into a structured artifact with optional spec linkage and deterministic planning outputs.

Do I need a specific project setup to generate structured work item files?▼

No specific setup is required beyond providing natural language input. You can optionally specify a project name to organize the generated work items, ensuring nothing gets lost in scattered notes across projects.

What is the best way to convert conversational notes into organized planning artifacts?▼

The best way to convert conversational notes into organized artifacts is using AI type detection to generate structured TASK, SPIKE, or BUG files that integrate with specs and deterministic planning outputs like PLAN and WORKLOG.

Can generated work items be linked to existing project specs?▼

Yes, generated work items support optional spec linkage, allowing standalone TASK, SPIKE, or BUG artifacts to integrate directly with existing project specs and planning workflows.

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