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aif-implement

Executes implementation tasks from plan files with progress tracking and session resumption.

Updated Jun 5, 2026
Search Tags:#git workflow#implementation#plan execution#progress tracking#task execution#session resume#coding automation
One-click install
npx skills add https://github.com/1t1sCooL/zazyvala-bot --skill aif-implement-1t1scool
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: aif-implement
Source: https://github.com/1t1sCooL/zazyvala-bot/tree/main/.cursor/skills/aif-implement
Command: npx skills add https://github.com/1t1sCooL/zazyvala-bot --skill aif-implement-1t1scool

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Turning a written implementation plan into actual code requires tracking which tasks are done, resuming after interruptions, and keeping plan checkboxes in sync with reality. This Skill automates that execution loop so multi-session coding work never loses progress. ## Core Features & Use Cases - Sequential Task Execution: Reads a plan file, works through tasks one at a time, marks them in_progress/completed, and updates - [ ] checkboxes to - [x] immediately after each task. - Session Persistence & Recovery: Rebuilds context from git state and plan files after /clear or a new session, reconciling TaskList statuses with plan checkboxes before continuing. - Plan Discovery & Routing: Auto-detects branch-named plans, fast plans, and fix plans, supports @plan-file overrides, --list mode, and redirects fix plans to the fix workflow. - Handoff & Artifact Sync: Syncs status with a Handoff coordinator via MCP tools, updates DESCRIPTION/ARCHITECTURE/ROADMAP artifacts when the stack or structure changes, and handles commit checkpoints and worktree merges. - Use Case: After running /aif-plan full Add user authentication, invoke this Skill across multiple sessions to implement all six tasks, commit at checkpoints, and finish with verification and roadmap milestone updates. ## Quick Start Ask the AI to run /aif-implement to continue executing the current plan from the next incomplete task.

Frequently Asked Questions about aif-implement

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

FAQPage Schema
How do I resume implementation after clearing the session?▼

Run /aif-implement again and it rebuilds context from git status, recent commits, and the plan file. It reconciles TaskList statuses with plan checkboxes, then continues from the next incomplete task automatically.

How do I execute a specific plan file instead of auto-detection?▼

Pass the file with the @ prefix, for example /aif-implement @.ai-factory/plans/feature-user-auth.md. The explicit path overrides branch-based and default plan discovery, and you can combine it with a task number or status argument.

What plan files does the implementation workflow detect?▼

It checks in priority order: an explicit @path argument, a branch-named plan in the configured plans directory, a single named full plan, the resolved fast plan path, and finally the fix plan path which redirects to the fix workflow.

Does the implementation skill write tests automatically?▼

No. Tests are only written when the plan explicitly includes test tasks. The skill's critical rules forbid creating tests, reports, or summary documents outside the planned task list.

What happens when all implementation tasks are complete?▼

The skill syncs final status to Handoff if linked, offers verification via /aif-verify or committing via /aif-commit, marks matching ROADMAP milestones complete, and optionally handles documentation checkpoints and worktree merge cleanup.

Why does the skill require verbose logging in generated code?▼

AI-generated code can contain subtle bugs that are hard to diagnose without logs. The skill mandates logging function entry/exit, state changes, external calls, and error context, all controllable through a LOG_LEVEL environment variable.

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