Convert vague app ideas into execution-ready technical specifications for AI coding agents.
npx skills add https://github.com/arpingblue/vibepm --skill vibepm
Please help me install this Agent Skill. Skill: vibepm Source: https://github.com/arpingblue/vibepm/tree/main Command: npx skills add https://github.com/arpingblue/vibepm --skill vibepm
## What problem does it solve? VibePM helps teams transform vague app ideas into precise, execution-ready technical specifications that AI coding agents can blindly implement, reducing hallucinations and scope creep.
## Core Features & Use Cases
### Quick Start To begin, describe your vague app idea and I will produce a complete Vibecoding plan.
High-intent search queries and answers about installing and using this skill.
You convert vague app ideas into AI-ready technical specifications by engaging in a structured dialogue that locks down the 9 core elements like tech stack, data schema, and MVP scope. This produces unambiguous plans that AI coding agents can execute without hallucinations.
Planning architecture for Cursor and Windsurf projects requires generating standardized artifacts like PROJECT.md, ROADMAP.md, and PLAN.md. These files provide concrete guardrails and execution-ready handoff documentation to guide safe downstream coding.
You generate a ROADMAP.md and data schema for vibecoding workflows by defining your app flow, state management, and edge cases through a structured planning process. This yields standardized templates ready for immediate execution by AI agents.
Yes, this architecture planning approach works with OpenClaw and similar AI agents by providing concrete artifacts and guardrails. It outputs execution-ready specifications that mitigate early risks and scope creep across various AI coding platforms.
AI coding agents hallucinate or cause scope creep during execution due to vague or ambiguous technical specifications. Converting your ideas into precise, structured plans with clear MVP scope cuts and edge case definitions prevents these downstream issues.
You need to create standardized artifacts like PROJECT.md for AI execution when you want ready-to-run handoff documentation. This ensures AI coding agents have the exact guardrails, data schemas, and deployment plans required to implement features safely.
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ianyimiEnforce coding standards for the global tech stack in Claude Code.
hernamesbarbaraGenerate READMEs, API references, user guides, ADRs, and runbooks from codebases.
