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create-implementation-plan

Generates structured Markdown implementation plans for features, refactoring, and upgrades.

1|1|Updated Jan 29, 2026
Search Tags:#template#planning#markdown#refactoring#feature development#ai agents#implementation plan
One-click install
npx skills add https://github.com/ultraviollettnympho/transit-ticket --skill create-implementation-plan-ultraviollettnympho
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: create-implementation-plan
Source: https://github.com/ultraviollettnympho/transit-ticket/tree/main/.github/skills/create-implementation-plan
Command: npx skills add https://github.com/ultraviollettnympho/transit-ticket --skill create-implementation-plan-ultraviollettnympho

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Writing implementation plans that both humans and AI agents can execute without ambiguity is difficult; this Skill produces deterministic, machine-readable plan files with a strict template so tasks can be executed autonomously. ## Core Features & Use Cases - Standardized Plan Template: Enforces a mandatory Markdown structure with front matter, requirements, phased tasks, dependencies, risks, and testing sections. - AI-Optimized Output: Uses explicit identifiers (REQ-, TASK-, GOAL-), tables, and validation rules so plans can be parsed and executed by other AI systems. - Use Case: When starting a new feature or package upgrade, ask the AI to draft an implementation plan and receive a complete /plan/ directory file with phases, task tables, status badges, and acceptance criteria ready for execution. ## Quick Start Ask the AI to create an implementation plan for your feature or refactoring goal, for example: create an implementation plan for adding user authentication to the app.

Frequently Asked Questions about create-implementation-plan

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

FAQPage Schema
How do I create an implementation plan for a new feature?▼

Invoke the Skill with the plan purpose, such as the feature name or refactoring goal. It generates a Markdown file in the /plan/ directory following the naming convention [purpose]-[component]-[version].md with all required template sections populated.

What structure should an AI-executable implementation plan follow?▼

The plan must include YAML front matter with goal, status, and tags, followed by sections for requirements, phased implementation steps with task tables, alternatives, dependencies, files, testing, and risks. All identifiers use standardized prefixes like REQ-, TASK-, and GOAL-.

Where are the generated implementation plan files saved?▼

Plan files are saved in the /plan/ directory using the naming convention [purpose]-[component]-[version].md. Purpose prefixes include upgrade, refactor, feature, data, infrastructure, process, architecture, and design.

Can AI agents execute the generated plans automatically?▼

Yes, the plans are designed for AI-to-AI communication with deterministic language, atomic phases, measurable completion criteria, and machine-parseable tables. Each task includes specific file paths and validation criteria requiring no human interpretation.

What status values are allowed in the plan front matter?▼

The status field accepts Completed, In progress, Planned, Deprecated, or On Hold. Each status also appears as a colored badge in the introduction section using shields.io badge URLs.

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