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10x-plan

Creates detailed implementation plans through iterative research and structured questioning.

Updated May 20, 2026
Search Tags:#implementation planning#progress tracking#technical specification#codebase research#clarifying questions#phased plan
One-click install
npx skills add https://github.com/ZawilecxD/trAInR --skill 10x-plan-zawilecxd
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: 10x-plan
Source: https://github.com/ZawilecxD/trAInR/tree/main/.cursor/skills/10x-plan
Command: npx skills add https://github.com/ZawilecxD/trAInR --skill 10x-plan-zawilecxd

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Writing implementation plans without sufficient codebase research or requirement clarification leads to costly rework and missed edge cases. This Skill guides an interactive, iterative planning process that grounds every plan in verified codebase facts and explicit user decisions. ## Core Features & Use Cases - Adaptive Questioning: Scales the number and focus of clarifying questions based on task complexity (LOW/MEDIUM/HIGH) and upstream artifacts like frame briefs and research docs, avoiding redundant questions. - Research-Driven Planning: Spawns parallel exploration agents to map relevant files, patterns, and prior decisions before writing, with file:line references embedded in the plan. - Structured Plan Output: Produces a phased plan.md with automated and manual success criteria, a plan-brief.md two-pager summary, and a machine-readable Progress section for execution tracking. - Use Case: A developer receives a ticket to add OAuth login. They invoke the skill with the change ID, answer a round of scoped questions about session handling and error states, and receive a phased implementation plan with verification steps ready for execution. ## Quick Start Ask the AI to create a detailed implementation plan for your task or ticket, optionally passing a change ID or path to an existing research or frame document.

Frequently Asked Questions about 10x-plan

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

FAQPage Schema
How do I create a detailed implementation plan with AI?▼

Invoke the skill with a task description, ticket reference, or change ID. It researches the codebase with parallel exploration agents, asks complexity-scaled clarifying questions, then writes a phased plan with automated and manual success criteria to context/changes/<change-id>/plan.md.

How does the skill decide how many questions to ask?▼

Question count scales with assessed complexity: LOW gets 4-6, MEDIUM 7-10, HIGH 11-15. Providing upstream artifacts reduces this further — a frame brief or research doc means questions already answered there are skipped.

Can I use existing research documents when planning?▼

Yes. Pass a research.md or frame.md path when invoking, and the skill treats them as authoritative. Research findings become the codebase baseline and frame briefs settle problem framing, so only unresolved solution-design questions are asked.

What files does the planning process produce?▼

It writes plan.md with phased changes and success criteria, plus plan-brief.md as a two-page summary with key decisions and scope. Both live in context/changes/<change-id>/, and change.md is updated to status: planned.

What are the limitations of this planning approach?▼

The skill refuses to write plans into archived change folders and requires user confirmation at complexity assessment and outline stages, so it is not fully autonomous. It also depends on the quality of upstream artifacts for question scaling.

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