research-plan-implement

Structure software development into research, planning, validation, implementation, and testing phases.

Updated Dec 18, 2025

Search Tags:#workflow #planning #documentation #research #codebase #implementation #agents

Ready to run

npx skills add https://github.com/seekayel/agent-skills --skill research-plan-implement

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: research-plan-implement
Source: https://github.com/seekayel/agent-skills/tree/main/plugins/research-plan-implement-plugin/research-plan-implement
Command: npx skills add https://github.com/seekayel/agent-skills --skill research-plan-implement

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a structured, multi-phase workflow to guide AI-assisted software development.

Core Features & Use Cases

Phases: Research, Plan, Validate, Implement, Test, with parallel agent support for faster insights.
Artifact Workflow: Generates and stores findings, plans, and validation artifacts in _thoughts folders.
Use Case: A team deploying a new feature can systematically research, plan, validate, implement, and verify changes using the skill.

Quick Start

Use the research-plan-implement skill to structure a codebase change from research to testing.

Frequently Asked Questions about research-plan-implement

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

FAQPage Schema

How do I structure an AI-driven codebase implementation from research to testing?▼

You can structure an AI-driven codebase implementation using a multi-phase workflow that covers research, planning, validation, implementation, and testing. It guides changes systematically while storing findings and validation artifacts in _thoughts directories.

What is the best way to plan software development using parallel agents?▼

Planning software development with parallel agents involves orchestrating multiple agents across research, plan, and validation phases to generate faster insights. This approach enforces structured outputs and tracks progress through validation checkpoints.

How does a phased workflow validate implementation plans before coding?▼

A phased workflow validates implementation plans by enforcing structured validation checkpoints between the planning and implementation stages. It generates validation artifacts stored in _thoughts folders to verify changes before actual coding begins.

Can I use this structured workflow for any codebase modification?▼

Yes, you can use this structured workflow for any codebase modification that requires systematic research, planning, and testing. It is designed to guide AI-assisted software development from initial research through final verification.

Where are research findings and implementation plans stored during the workflow?▼

Research findings and implementation plans are stored as structured artifacts in _thoughts directories within the codebase. This artifact workflow ensures that multi-phase development outputs are systematically saved and tracked.

Why use a structured workflow for AI-assisted software development instead of direct prompting?▼

Using a structured workflow solves fragmented software development planning by enforcing phased implementation, validation checkpoints, and parallel agent orchestration. Direct prompting lacks this systematic progress tracking and artifact generation across research and testing.