ai-native-implementation-plan
Use when converting a clarified software problem into an MVP-first phased roadmap with scope, risks, dependencies, and validation criteria.
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- Signed
Install this skill
Run this command in your terminal. No account required — it auto-detects your AI tool and installs the skill file.
npx @skills-hub-ai/cli install ai-native-implementation-planSetup by platform
Install
One-click setup for your editorRun in your project root
npx @skills-hub-ai/cli install ai-native-implementation-plan --target claude-codeExamples
Prompt
I want to build a chatbot that helps users schedule meetings. Can you create a phased plan?Output
# Meeting Scheduler Chatbot Implementation Plan
## Problem Traceability
Aimed to assist users in scheduling meetings via a conversational interface, reducing manual effort and errors.
## MVP Definition
### Hypothesis
A simple chatbot can collect meeting details and suggest available times, validating if users prefer automated scheduling.
### Included
A basic conversational interface that gathers date, time, and participants.
### Excluded
Calendar integrations, reminders, and multi-platform deployment.
### First Testable State
A web-based chatbot that interacts with users to gather meeting info and proposes times.
## Recommended Tech Stack
Node.js with Express, React for frontend, and a simple NLP library like Rasa or Dialogflow.
## Phase 1 - MVP
### Objective
Validate if a basic chatbot can collect meeting details and suggest times.
### Scope
Web interface, basic NLP for intent detection, static availability data.
### Deliverables
Working chatbot collecting inputs and displaying suggested times.
### Dependencies
Hosting environment, NLP service setup.
### Risks
Misinterpretation of user inputs, limited availability data.
### Validation Criteria
User testing shows successful data collection and correct suggestions in 80% of interactions.
## Phase 2 - Expansion
Add calendar integration and user authentication.
## Phase 3 - Further Features
Implement multi-platform support and automated reminders.
## Open Questions
What are the target platforms? Is real-time calendar access required?
Prompt
Plan an MVP for a mobile app that tracks daily water intake. How should I proceed?Output
# Water Intake Tracker Implementation Plan
## Problem Traceability
Users forget to drink water regularly; a simple app can remind and log intake to promote hydration.
## MVP Definition
### Hypothesis
A minimal app that allows users to log daily water intake and view totals will increase hydration awareness.
### Included
Basic logging feature, daily total display, simple UI.
### Excluded
Barcode scanning, social sharing, detailed analytics.
### First Testable State
A mobile app where users can log water intake and see daily totals.
## Recommended Tech Stack
React Native for cross-platform development, local storage for data, minimal backend if needed.
## Phase 1 - MVP
### Objective
Test if users will log water intake and find the interface usable.
### Scope
Logging feature, daily total view, local data storage.
### Deliverables
Functional app with input button and total display.
### Dependencies
Mobile development environment, testing devices.
### Risks
Low user engagement, data loss.
### Validation Criteria
At least 50 users log water at least once daily in a week.
## Phase 2 - Expansion
Add reminders and history view.
## Phase 3 - Further Features
Implement goal setting and social sharing.
## Open Questions
Should the app sync with health apps? What are the target user demographics?
Instructions
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Frequently asked questions about ai-native-implementation-plan
What does the ai-native-implementation-plan skill do?
Use when converting a clarified software problem into an MVP-first phased roadmap with scope, risks, dependencies, and validation criteria. It's a reusable SKILL.md instruction set that loads into your AI coding assistant on demand, no prompt engineering, no copy-pasting every session.
How do I install the ai-native-implementation-plan skill?
Run `npx @skills-hub-ai/cli install ai-native-implementation-plan` from your terminal. The CLI writes the SKILL.md to the correct location for your AI tool (e.g. ~/.claude/skills/ai-native-implementation-plan/ for Claude Code or ~/.cursor/skills/ for Cursor with --target cursor) and adds it to your project's .skills.json lockfile.
Which AI tools does ai-native-implementation-plan work with?
ai-native-implementation-plan runs in Claude Code, Cursor, Codex CLI. It follows the open Agent Skills standard (SKILL.md), so the same skill works in every supported tool without modification.
Is the ai-native-implementation-plan skill free?
Yes. Every skill on skills-hub.ai is free and open-source. There are no premium tiers, paywalls, or usage limits. You only pay for whatever AI assistant you're already using.
How do I use ai-native-implementation-plan after installing it?
In Claude Code, type `/ai-native-implementation-plan` (or whatever slash command the skill registers) and the AI follows the skill's instructions immediately. You can also reference it by name in natural language, your AI loads the skill into context when relevant.
Can I share the ai-native-implementation-plan skill with my team?
Yes. Commit your project's .skills.json lockfile and teammates run `npx @skills-hub-ai/cli install` (no args) to install every skill at the exact version you pinned. Organization-scoped installs work via skills-hub.ai organizations.