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Converts raw user input into a tight, structured prompt capped at about 200 tokens to reduce model drift. Use when the user wants a short, reusable prompt, asks to "light prompt" or compress a request, or when downstream calls need a minimal instruction block.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Researches requirements when needed, then plans, organizes, and structures content without coding or implementation. Use when creating project plans, structuring workflows, organizing tasks, building implementation roadmaps, or when planning features before execution.
Builds execution-ready Task dispatch from planning skill outputs—one Task per todo, phased barriers, parallel_group batches, and handoffs. Use after `.cursor/plans/{objective}.plan.md` exists or when converting phased todos into concrete Task prompts before delegation.
Maintains npm libraries: audits uncommitted work for security and conventions, splits changes into logical commits and semver releases, updates changelogs and package.json version, then pushes. Use when releasing or maintaining an npm package, publishing a library, or the user asks for version bumps, changelog updates, or structured commits before push.
Professional UI/UX-focused agent specializing in modern interface design, user experience optimization, design system adherence, and accessibility standards. Use when designing interfaces, improving user experience, creating UI components, ensuring design consistency, or implementing accessibility features.
Conducts thorough research and analysis of task requirements before implementation. Use when the user wants comprehensive research, codebase analysis, or needs to understand a task completely before coding.
Build a deterministic end-to-end flow plan file for a user objective using the /unravel command. Use when the user asks for /unravel, asks to map full flow, or needs architecture plus sequence/state diagrams and a traceable execution narrative.
| name | light-prompt |
| description | Converts raw user input into a tight, structured prompt capped at about 200 tokens to reduce model drift. Use when the user wants a short, reusable prompt, asks to "light prompt" or compress a request, or when downstream calls need a minimal instruction block. |
Longer instructions increase off-task behavior. This skill trades elaboration for clarity and boundaries.
**Technique (research-backed, compressed)**Effective short prompts combine:
@path (e.g. @folder/file, @src/component.vue). List only paths the model must read.Omit sections that add no information. Be direct; avoid clever phrasing.
Token budget
Return
Return only the finished prompt text (no meta commentary), using the skeleton in <example> when it fits.
Use shorter labels or merge lines if needed to stay under the cap.
Task: …Context:
Before returning:
@file paths when applicable.