microcopy

Standardizes multilingual UI microcopy for Hub-like platforms with fixed terminology and tone rules.

1|Updated May 9, 2026
One-click install
npx skills add https://github.com/duwenji/generative-ai-oss-tutorials --skill microcopy-duwenji
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: microcopy
Source: https://github.com/duwenji/generative-ai-oss-tutorials/tree/main/sandbox/lobe-chat/.agents/skills/microcopy
Command: npx skills add https://github.com/duwenji/generative-ai-oss-tutorials --skill microcopy-duwenji

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill solves inconsistent, unclear, or non-actionable user-facing UI copy by providing brand-aligned microcopy rules for titles, buttons, errors, onboarding, empty states, and other on-screen guidance.

Core Features & Use Cases

  • UI copy consistency: Enforces fixed terminology and consistent verbs for key flows (Create / Connect / Run / Pause / Retry / View details / Clear Memory).
  • Tone and warmth control: Applies an 80/20 warmth-to-information approach, with stricter warmth caps at sensitive moments like failures, long waits, and empty states.
  • Actionable error patterns: Requires every error to include what happened, an optional why, and clear next steps (e.g., Retry / View details / Go to Settings / Copy logs).
  • CN i18n → EN localization: Translates raw Chinese UI strings into natural English while keeping meaning, placeholders, and length constraints in mind.

Quick Start

Translate a Chinese UI string to English while preserving placeholders and making the result equally actionable and length-aware.

Frequently Asked Questions about microcopy

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

FAQPage Schema
How do I write clearer UI copy for error messages and empty states?

To write clearer UI copy for error messages and empty states, ensure every error states what happened, an optional why, and clear next steps like Retry or View details. Maintain an 80/20 warmth-to-information ratio, using stricter tone caps for sensitive moments.

What is the best way to localize Chinese UI strings to English while preserving placeholders?

Localizing Chinese UI strings to English requires translating raw text into natural English while keeping meaning, placeholders, and length constraints intact. This ensures the localized UI copy remains equally actionable and correctly structured for the English interface.

How do I standardize UI microcopy for consistent terminology across onboarding flows?

Standardizing UI microcopy for onboarding flows involves enforcing fixed term mappings and consistent verbs like Create, Connect, Run, Pause, and Clear Memory. This ensures clarity and consistent terminology across all multilingual user guidance scenarios.

What tone should I use for long-wait messages and collaborative agent flows?

For long-wait messages and collaborative agent flows, apply an 80/20 warmth-to-information approach with stricter warmth caps. This calmer UI text guides action effectively without overwhelming the user during sensitive or delayed processing moments.

Does UI microcopy need to follow specific brand tone rules for internationalization?

Yes, UI microcopy requires adherence to fixed brand tone rules for internationalization. These rules standardize terminology, control warmth-to-information ratios, and enforce structured error requirements to ensure clear, actionable user guidance across multilingual screens.

Why does my i18n translation break interface layouts with length constraints?

I18n translation often breaks layouts when English text expands beyond original Chinese length constraints. Proper UI microcopy localization translates strings to natural English while actively preserving placeholders and managing length to prevent interface formatting issues.