error-states
Design error states that help users understand what went wrong and how to recover, while preserving trust. Use when specifying form errors, system failures, permission issues, or any failure UI.
- License 许可
- MIT
- 最近更新
- 2026-07-22
- Stars
- ★ 7
- Forks
- 1
01 前言 Front Matter
- name
- error-states
- description
- Design error states that help users understand what went wrong and how to recover, while preserving trust. Use when specifying form errors, system failures, permission issues, or any failure UI.
03 SKILL.md 正文
Error States
Overview
Errors are emotional moments. Good error design reduces frustration, enables recovery, and protects trust. Bad error design blames the user or leaves them stuck.
When to Use
- Form validation and input errors
- System/network/server failures
- Permission and authorization failures
- Not-found and expired-link states
- Destructive action confirmations gone wrong
Core Practices
- Say what happened in plain language
- Say how to fix it or what to try next
- Preserve user input whenever possible
- Use appropriate severity (inline vs page-level vs blocking modal)
- Log and monitor errors that indicate product problems
- Design for both user mistakes and system failures
Principles
- Never blame the user
- Be specific — “Something went wrong” is not enough when you can say more
- Offer a path forward (retry, contact support, go back, edit)
- Match tone to severity
Verification
- [ ] User knows what failed and what to do next
- [ ] Recovery paths exist for common errors
- [ ] Input isn’t needlessly wiped
04 同仓库更多 Skills
compliance-monitoring
Design compliance monitoring and testing programs that verify controls work in practice and surface issues before regulators do. Use when building monitoring plans, compliance testing, or continuous control monitoring.
complaints-handling
Operate complaints-handling processes that meet regulatory standards — logging, timely resolution, root-cause analysis, and fair outcomes. Use when designing or improving regulated complaints frameworks or analyzing complaint themes for conduct risk.
aml-kyc-basics
Apply AML/KYC fundamentals — customer due diligence, monitoring, suspicious activity escalation, and recordkeeping — for financial crime compliance. Use when designing onboarding controls, transaction monitoring concepts, or AML program components in financial services.
ai-model-compliance
Apply compliance controls to AI and automated decision systems — transparency, fairness, human oversight, documentation, and regulatory alignment. Use when deploying AI in regulated processes (credit, fraud, customer decisions) or responding to AI governance expectations.
data-quality-management
Manage data quality end-to-end — dimensions, rules, remediation, and prevention — beyond one-off cleaning scripts. Use when building sustained data quality programs or fixing systemic accuracy, completeness, or consistency problems.
data-lineage
Capture and use data lineage — where data comes from, how it transforms, and what depends on it — for impact analysis, debugging, and trust. Use when tracing metric origins, assessing change impact, or diagnosing broken pipelines.