ai-factory.feature

Create feature branches and generate plans within a Git workflow.

1.1k|92|Updated Feb 6, 2026
One-click install
npx skills add https://github.com/lee-to/ai-factory --skill ai-factory-feature
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ai-factory.feature
Source: https://github.com/lee-to/ai-factory/tree/main/skills/feature
Command: npx skills add https://github.com/lee-to/ai-factory --skill ai-factory-feature

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automates the initiation of feature development in a Git-based project by creating descriptive branches, planning tasks, and collecting user preferences before execution.

Core Features & Use Cases

  • Create descriptive feature branches (e.g., feature/user-authentication) based on user input.
  • Generate planning files and orchestrate task planning via /ai-factory.task with explicit context.
  • Prompt for testing and logging preferences before executing plans to ensure guardrails and traceability.

Quick Start

Describe the feature to begin, and the agent will create a branch, generate a plan file, and prompt about tests and logging.

Frequently Asked Questions about ai-factory.feature

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

FAQPage Schema
How do I automate feature branch creation and task planning in a Git workflow?

Feature branch creation and task planning are automated by generating descriptive branch names and plan files from user input. The workflow enforces branch naming rules and orchestrates subsequent tasks via explicit context calls.

What is the best way to start feature development with AI-assisted branch management?

AI-assisted feature development begins by describing the feature to the agent. It creates a descriptive branch, generates a planning file, and prompts for testing and logging preferences to ensure guardrails and traceability.

Do I need to manually set up testing and logging preferences before executing a feature plan?

Testing and logging preferences are prompted automatically before plan execution. The agent collects these user preferences to ensure guardrails and traceability are established before any tasks are orchestrated.

Can I use this feature planning workflow for request-driven feature creation?

Request-driven feature creation is fully supported by this workflow. It applies to user prompts and validation to automate the initiation of feature development within a Git-based project environment.

How does branch naming work when initiating a new feature development task?

Branch naming enforces specific rules to create descriptive branches like feature/user-authentication based on user input. This ensures consistent branch management before generating planning files and orchestrating tasks.

What happens after the feature branch is created and the plan is generated?

After branch creation and plan generation, the agent orchestrates subsequent tasks via /ai-factory.task calls. This orchestration uses explicit context to drive the feature development forward.