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phased-plan

Generate implementation-ready phased plans for complex software tasks using TDD.

1|Updated Apr 9, 2026
Search Tags:#workflow#planning#tdd#codebase#verification#orchestration
One-click install
npx skills add https://github.com/hadi-technology/phased-workflow --skill phased-plan-hadi-technology
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: phased-plan
Source: https://github.com/hadi-technology/phased-workflow/tree/main/skills/phased-plan
Command: npx skills add https://github.com/hadi-technology/phased-workflow --skill phased-plan-hadi-technology

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill solves the problem of AI agents drifting from intent and producing unverified, low-quality code by enforcing a structured, multi-phase planning and execution workflow.

Core Features & Use Cases

  • Phased Decomposition: Breaks complex feature requests into independently verifiable, testable slices.
  • Empirical Verification: Mandates TDD, regression testing, and explicit evidence gathering before implementation.
  • Use Case: Use this when building a complex new feature to ensure the architecture is sound, risks are mitigated, and every step is independently validated by the agent before moving to the next phase.

Quick Start

Invoke the phased-plan skill to generate an implementation plan for the requested feature by providing the task requirements and codebase context.

Frequently Asked Questions about phased-plan

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

FAQPage Schema
How do I generate a phased implementation plan for complex software features?▼

To generate a phased implementation plan, you provide task requirements and codebase context. The skill decomposes complex features into independently verifiable slices, applying risk-scaled precision and structural cleanliness gates for autonomous execution.

What is the best way to enforce TDD and empirical verification in AI code generation?▼

The best way to enforce TDD in AI code generation is using a structured workflow that mandates empirical discovery, regression testing, and explicit evidence gathering before implementation proceeds to the next phase.

Can I use this for architectural refactoring and bug-fix sweeps?▼

Yes, you can use this for architectural refactoring and bug-fix sweeps. The skill applies empirical discovery and test-driven development to orchestrate autonomous, verifiable code execution across multi-phase development tasks.

How do you prevent AI agents from drifting from intent during codebase development?▼

You prevent AI agents from drifting from intent by enforcing a structured, multi-phase planning and execution workflow. This ensures every step is independently validated by the agent before moving forward, producing verifiable code.

Do I need to provide codebase context to get an implementation-ready workflow?▼

Yes, you need to provide codebase context and task requirements. The skill uses this input to perform empirical discovery, generating an implementation-ready workflow that satisfies requirements for independent verification.

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