implement-feature

Orchestrates wave-based parallel coder agents with code-review gates for feature specs.

Updated May 14, 2026
One-click install
npx skills add https://github.com/LeroyAdonis/vector --skill implement-feature-leroyadonis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: implement-feature
Source: https://github.com/LeroyAdonis/vector/tree/main/.agents/skills/implement-feature
Command: npx skills add https://github.com/LeroyAdonis/vector --skill implement-feature-leroyadonis

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Orchestrate the parallel implementation of a feature specification by dispatching coder agents wave-by-wave with code review gates between waves. The orchestrator does not write code itself; it coordinates tasks, context, and reviews to ensure quality while enabling scalable collaboration.

Core Features & Use Cases

  • Wave-based orchestration: Dispatches parallel coder agents for each task in a wave and gates results with a code-review step before moving to the next wave.
  • Spec-driven workflows: Reads a specs/{feature}/ folder containing README.md, requirements.md, and task-*.md files to guide work.
  • Resumable progress & governance: Picks up exactly where it left off and tracks task statuses across waves, with built-in review loops.

Quick Start

Provide a specs/{feature} folder and run the orchestrator to begin the feature's wave-by-wave implementation.

Frequently Asked Questions about implement-feature

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

FAQPage Schema
How do I orchestrate parallel coding agents for feature implementation?▼

Parallel coding agent orchestration dispatches coder agents wave-by-wave, using code review gates between waves to ensure quality before advancing to subsequent tasks.

What is a spec-driven workflow for parallel feature builds?▼

A spec-driven workflow reads a specs/{feature}/ folder containing README.md, requirements.md, and task files to provide context and guide parallel coder agents through implementation.

How do I resume a parallel feature build after stopping midway?▼

Resuming a parallel feature build works by picking up exactly where the orchestrator left off, tracking task statuses across waves in the spec files to continue execution seamlessly.

Can I run feature implementation tasks in parallel without manual code review gates?▼

Feature implementation requires a single code-review gate after each wave of parallel tasks, ensuring quality control before advancing to the next set of dispatched coder agents.

Does the orchestrator write code directly during spec implementation?▼

The orchestrator never writes code itself during spec implementation; it only provides task context, collects results, handles fix loops, and records progress in the spec files.

What file structure is needed to start a wave-based feature implementation?▼

Wave-based feature implementation requires a specs/{feature}/ folder containing README.md, requirements.md, and task-*.md files to define the work for the coder agents.