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aif-implement

Execute plan-based tasks sequentially with progress tracking and session recovery.

56|3|Updated Mar 17, 2026
Search Tags:#automation#workflow#recovery#plan#progress#implement#task
One-click install
npx skills add https://github.com/lee-to/ai-workspace --skill aif-implement-lee-to
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: aif-implement
Source: https://github.com/lee-to/ai-workspace/tree/main/.claude/skills/aif-implement
Command: npx skills add https://github.com/lee-to/ai-workspace --skill aif-implement-lee-to

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill automates the end-to-end execution of tasks defined in a plan, managing progress across sessions and resuming where you left off.

Core Features & Use Cases

  • Sequential task execution: processes tasks one at a time in the defined plan.
  • State management: marks tasks as in_progress and completed, and updates plan checkboxes to reflect progress.
  • Plan discovery & resumption: supports explicit plan files, branch-named plans, and auto-discovery from .ai-factory plan files.
  • Session continuity: preserves progress across sessions and recovers from breaks without losing state.
  • Project-wide impact: updates related metadata (.ai-factory/DESCRIPTION.md, ARCHITECTURE.md) when the scope changes.

Quick Start

Run /aif-implement to resume the next pending task and follow on-screen prompts.

Frequently Asked Questions about aif-implement

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

FAQPage Schema
How do I resume task execution from a plan after closing my session?▼

Persistent progress tracking records task state transitions and updates plan checkboxes automatically, allowing you to resume the next pending task exactly where you left off after a session break.

How does automated plan discovery work for project feature development?▼

Plan discovery locates your project feature development tasks by checking explicit plan files, branch-named plans, and auto-discovery from .ai-factory directories without manual configuration.

Can I execute plan tasks sequentially and track their completion state?▼

Sequential task execution processes plan items one at a time, managing state transitions by marking tasks as in_progress and completed while updating checkboxes in the plan file.

Do I need a specific plan file format to automate task implementation?▼

Task implementation automation supports explicit plan files, branch-named plans, and auto-discovered plans from .ai-factory directories, accommodating various project documentation setups.

What happens to project metadata when task scope changes during implementation?▼

When scope changes occur during task implementation, the workflow coordinates optional metadata updates to project documentation, modifying .ai-factory/DESCRIPTION.md and ARCHITECTURE.md files.

What are the limitations of automating plan-based task execution?▼

Task execution automation focuses on sequential processing of defined plan tasks and requires plan files or .ai-factory directories for discovery, limiting parallel execution and ad-hoc task support.

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