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Agent Skill · 前端设计

error-sanitization(错误清理)

error-sanitization 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 Codex、Claude、Cursor、Gemini CLI 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

error-sanitization 是前端设计类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在前端设计类的 10,216 个 Skill 里排第 6,376。

总安装 517周安装 22GitHub Stars 777下载 181核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:error-sanitization(错误清理)
来源仓库:https://github.com/dadbodgeoff/drift
仓库路径:skills/error-sanitization
安装命令:
npx skills add https://github.com/dadbodgeoff/drift --skill error-sanitization
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/dadbodgeoff/drift --skill error-sanitization

这个 Skill 是做什么的

前端设计类 Skill 关注页面结构、视觉规范和组件写法,输出通常是可运行的界面代码。

error-sanitization 确保生产环境中错误消息不暴露敏感信息,全部日志留存服务端。适用于 API 网关、批处理作业等需对外返回错误但又要保护隐私的场景。指导如何剥离连接字符串、路径和堆栈轨迹,仅返回通用提示。安装方式:通过 npx 从 GitHub 仓库添加,需配置日志中间件或拦截器。

必须配合完善的日志收集系统,否则失去调试价值。

来源仓库内路径:skills/error-sanitization

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/dadbodgeoff/drift --skill error-sanitization;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

error-sanitization 怎么安装?

在终端执行 npx skills add https://github.com/dadbodgeoff/drift --skill error-sanitization。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

error-sanitization 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

error-sanitization 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

error-sanitization 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

error-sanitization 用的人多吗?

公开数据是累计安装 517 次,近一周安装 22 次,下载 181 次,GitHub 777 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

error-sanitization 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理前端设计类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

前端设计类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
frontend-design

前端设计 · Codex、Claude

8,823,360126,072只读MIT通过
vercel-composition-patterns

Vercel 组合模式 · Codex、Claude

3,858,81625,893需要联网MIT通过
vercel-react-native-skills

Vercel React native skills 前端 · Codex、Claude

2,468,66425,878只读MIT通过
adapt

adapt 搜索 · Codex、Claude

2,027,04023,125操作浏览器未明确通过
bolder

bolder 分析 · Codex、Claude

2,004,28823,130只读未明确通过
error-sanitization

错误清理 · 本页

517777需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Error Sanitization

Production-safe error handling: log everything server-side, expose nothing sensitive to users.

When to Use This Skill

  • Building APIs that return error messages to clients
  • Handling exceptions in production environments
  • Processing batch operations with partial failures
  • Any system where error messages could leak sensitive information

Core Concepts

Error messages can leak sensitive information including database connection strings, internal file paths, stack traces, API keys, and business logic details. The solution is to always log full error details server-side for debugging while returning only generic, safe messages to users.

The flow is:

  1. Exception occurs
  2. Log FULL error server-side with context
  3. Classify error type
  4. Return GENERIC message to user
  5. Only expose safe, actionable errors (like validation)

Implementation

Python

import os
import logging
from typing import Optional
from fastapi import HTTPException
from pydantic import ValidationError

logger = logging.getLogger(__name__)

class ErrorSanitizer:
    """
    Sanitizes error messages to prevent information leakage.
    """

    SENSITIVE_PATTERNS = [
        "password", "secret", "key", "token", "credential",
        "postgresql://", "mysql://", "mongodb://", "redis://",
        "localhost", "127.0.0.1", "internal", "0.0.0.0",
        "traceback", "exception", "error at", "line ",
        "/home/", "/var/", "/etc/", "C:\\",
        "SUPABASE", "AWS", "STRIPE", "SENDGRID",
    ]

    @staticmethod
    def is_production() -> bool:
        return os.getenv("ENVIRONMENT", "development").lower() == "production"

    @staticmethod
    def sanitize_error(
        e: Exception,
        user_message: str = "Operation failed",
        log_context: Optional[dict] = None
    ) -> str:
        """Sanitize error message for user display."""
        # ALWAYS log full error server-side
        logger.error(
            f"Error occurred: {type(e).__name__}: {str(e)}",
            exc_info=True,
            extra=log_context or {}
        )

        # In development, show more details
        if not ErrorSanitizer.is_production():
            return f"{user_message}: {str(e)}"

        # Validation errors are safe (user input issues)
        if isinstance(e, ValidationError):
            return f"Validation error: {str(e)}"

        # HTTPException with client error (4xx) is safe
        if isinstance(e, HTTPException):
            if 400 <= e.status_code < 500:
                return e.detail
            return user_message

        # Check for sensitive patterns
        error_str = str(e).lower()
        for pattern in ErrorSanitizer.SENSITIVE_PATTERNS:
            if pattern in error_str:
                return user_message

        # Short, simple errors without sensitive patterns might be safe
        if len(str(e)) < 100 and not any(c in str(e) for c in ['/', '\\', '@', ':']):
            return str(e)

        return user_message

    @staticmethod
    def create_http_exception(
        e: Exception,
        status_code: int = 500,
        user_message: str = "Operation failed",
        log_context: Optional[dict] = None
    ) -> HTTPException:
        """Create HTTPException with sanitized error message."""
        safe_message = ErrorSanitizer.sanitize_error(e, user_message, log_context)
        return HTTPException(status_code=status_code, detail=safe_message)

TypeScript

import { Logger } from './logger';

const SENSITIVE_PATTERNS = [
  'password', 'secret', 'key', 'token', 'credential',
  'postgresql://', 'mysql://', 'mongodb://', 'redis://',
  'localhost', '127.0.0.1', 'internal', '0.0.0.0',
  '/home/', '/var/', '/etc/', 'C:\\',
];

interface SanitizeOptions {
  userMessage?: string;
  logContext?: Record<string, unknown>;
}

export class ErrorSanitizer {
  private static isProduction(): boolean {
    return process.env.NODE_ENV === 'production';
  }

  static sanitize(
    error: Error,
    options: SanitizeOptions = {}
  ): string {
    const { userMessage = 'Operation failed', logContext = {} } = options;

    // Always log full error server-side
    Logger.error('Error occurred', {
      name: error.name,
      message: error.message,
      stack: error.stack,
      ...logContext,
    });

    // In development, show more details
    if (!this.isProduction()) {
      return `${userMessage}: ${error.message}`;
    }

    // Check for sensitive patterns
    const errorStr = error.message.toLowerCase();
    for (const pattern of SENSITIVE_PATTERNS) {
      if (errorStr.includes(pattern)) {
        return userMessage;
      }
    }

    // Short, simple errors might be safe
    if (error.message.length < 100 && !/[\/\\@:]/.test(error.message)) {
      return error.message;
    }

    return userMessage;
  }

  static createHttpError(
    error: Error,
    statusCode: number = 500,
    options: SanitizeOptions = {}
  ): { statusCode: number; message: string } {
    return {
      statusCode,
      message: this.sanitize(error, options),
    };
  }
}

Usage Examples

Route Handler

@router.post("/process")
async def process_invoice(invoice_id: str):
    try:
        result = await processor.process(invoice_id)
        return result
    except ValidationError as e:
        # Validation errors are safe to expose
        raise HTTPException(status_code=400, detail=str(e))
    except HTTPException:
        raise  # Re-raise as-is
    except Exception as e:
        # All other errors get sanitized
        raise ErrorSanitizer.create_http_exception(
            e,
            status_code=500,
            user_message="Failed to process invoice",
            log_context={"invoice_id": invoice_id}
        )

Domain-Specific Sanitizers

def sanitize_database_error(e: Exception) -> str:
    return ErrorSanitizer.sanitize_error(
        e,
        user_message="Database operation failed. Please try again.",
        log_context={"error_type": "database"}
    )

def sanitize_api_error(e: Exception, service_name: str = "external service") -> str:
    return ErrorSanitizer.sanitize_error(
        e,
        user_message=f"Failed to communicate with {service_name}.",
        log_context={"error_type": "external_api", "service": service_name}
    )

Batch Operations with Partial Failures

def process_items(items: list[dict]) -> dict:
    failed_items = []

    for idx, item in enumerate(items):
        try:
            process_item(item)
        except Exception as e:
            error_type = classify_error(e)
            failed_items.append({
                "line": idx,
                "description": item['description'][:50],  # Truncate
                "error_type": error_type,
                "message": get_user_friendly_message(error_type)
                # NOTE: Don't include str(e) - might be sensitive
            })

    return {
        "status": "partial_success" if failed_items else "success",
        "failed_items": failed_items
    }

Best Practices

  1. Always log full error details server-side with exc_info=True
  2. Include correlation IDs (request_id, session_id) in logs for tracing
  3. Truncate user input in error messages to prevent log injection
  4. Test error handling in production mode - errors look different in dev vs prod
  5. Monitor "unknown" error rates - high rates indicate missing classification

Common Mistakes

  • Exposing raw exception messages to users in production
  • Forgetting to log the full error before sanitizing
  • Including sensitive data in log messages (passwords, connection strings)
  • Not testing error responses in production mode
  • Trusting that "safe" errors don't contain injected content

Related Patterns

  • exception-taxonomy - Hierarchical exception system with error codes
  • circuit-breaker - Prevent cascading failures
  • error-handling - General error handling patterns

平台分布

Codex

36.88%
按下载量换算67

Claude

27.2%
按下载量换算49

Cursor

16.67%
按下载量换算30

Gemini CLI

9.32%
按下载量换算17

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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