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observability-testing可观察性测试

Agent Skill

用于辅助测试设计、自动化测试、用例整理和回归验证。它适合让 Agent 编写单元测试、端到端测试、测试计划或根据失败日志定位问题。使用时需要确认项目测试框架、运行命令和夹具数据,避免为了通过测试而改坏真实逻辑;涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。

总安装

294

周安装

12

GitHub Stars

5

下载量

95
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:observability-testing(可观察性测试)
来源仓库:https://github.com/apankov1/quality-engineering
仓库路径:skills/observability-testing
安装命令:
npx skills add https://github.com/apankov1/quality-engineering --skill observability-testing
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/apankov1/quality-engineering --skill observability-testing

简介

用于辅助测试设计、自动化测试和回归验证,适合在 Codex、Claude、Cursor、Gemini CLI 中编写测试用例或定位问题。

  • 适用于编写单元测试、端到端测试或根据失败日志定位问题的场景。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装并使用。
  • 使用时需确认项目测试框架和运行命令,避免为了通过测试而改坏真实逻辑。
  • observability-testing 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Observability Testing

Test that your code produces correct logs — not just that it runs.

Logs are your only window into production behavior. If critical paths don't log correctly, you're flying blind during incidents. This skill teaches you to verify structured log output as part of your test suite.

When to use: Testing error logging with context, audit trails, monitoring integration, log level policy enforcement, any code where observability matters.

When not to use: Pure business logic tests, UI components, tests where logging is incidental not critical.

Rationalizations (Do Not Skip)

RationalizationWhy It's WrongRequired Action
"Logs are side effects, not behavior"Incorrect logs = blind in productionAssert log output as first-class behavior
"I can see logs when I run it"Manual inspection doesn't scaleAutomate with mock logger assertions
"Any log level is fine"Wrong levels = alert fatigue or missed incidentsEnforce log level policy
"Context isn't important"Context-free logs are useless for debuggingAssert required context fields

What To Protect (Start Here)

Before generating log assertions, identify which observability decisions apply to your code:

DecisionQuestion to AnswerIf Yes → Use
Error paths must be debuggable from logs aloneCould an on-call engineer diagnose this failure without access to the request?assertLogEntry with context fields
Happy paths must not trigger alertsWould a warn/error log here fire a PagerDuty alert on every success?assertNoLogsAbove
Log levels must match operational severityIs this log classified correctly — would the wrong level cause alert fatigue or missed incidents?classifyLogLevel
Error logs must include the Error instanceDoes the error log carry a stack trace for root cause analysis?assertErrorLogged

Do not generate tests for decisions the human hasn't confirmed. A log assertion that checks "error was logged" without verifying the context contains fields an on-call engineer needs is slop — it passes while the team stays blind in production.


Included Utilities

import {
  createMockLogger,
  assertLogEntry,
  assertNoLogsAbove,
  assertHasLogLevel,
  assertErrorLogged,
  LOG_LEVEL_POLICY,
  LOG_LEVEL_ORDER,
  classifyLogLevel,
} from './structured-logger.ts';

Core Workflow

Step 1: Create Mock Logger

Replace real loggers with mock loggers that capture entries for assertion:

const logger = createMockLogger();

// Pass to code under test
await myHandler({ logger });

// Assert on captured entries
assert.equal(logger.entries.length, 2);

Step 2: Assert Specific Log Entries

Verify that specific logs were recorded with correct level, message, and context:

it('logs error with full context on failure', async () => {
  const logger = createMockLogger();

  await assert.rejects(() => myHandler({ logger, shouldFail: true }));

  assertLogEntry(logger, 'error', 'Request failed', {
    component: 'Handler',
    path: '/api/test',
  });
});

Step 3: Verify Happy Path Has No Warnings/Errors

Happy paths should not produce warnings or errors — that's alert fatigue:

it('happy path produces no warnings or errors', async () => {
  const logger = createMockLogger();

  await myHandler({ logger });

  assertNoLogsAbove(logger, 'info');  // Only debug/info allowed
});

Step 4: Verify Error Logs Include Error Instances

Error logs should include the actual Error object for stack traces:

it('error log includes Error instance', async () => {
  const logger = createMockLogger();

  try {
    await myHandler({ logger, causeError: true });
  } catch {}

  assertErrorLogged(logger, 'Database connection failed', {
    name: 'ConnectionError',
    message: 'timeout',
  });
});

Step 5: Follow Log Level Policy

Use the correct log level based on the nature of the message:

// Reference table
console.log(LOG_LEVEL_POLICY);
/*
{
  error: {
    description: "Actionable failures requiring investigation",
    examples: ["Database connection failed", "Authentication error"],
    production: "100% always",
  },
  warn: {
    description: "Degraded but recoverable",
    examples: ["Retry exhausted but fallback worked", "Deprecated API called"],
    production: "100% always",
  },
  info: {
    description: "Significant state changes",
    examples: ["User logged in", "Config loaded", "Session started"],
    production: "sampled (1-10%)",
  },
  debug: {
    description: "Routine operations",
    examples: ["Cache hit/miss", "Heartbeat tick", "Request timing"],
    production: "off (or LOG_LEVEL=warn)",
  },
}
*/

Step 6: Classify Log Levels Automatically

Use the classifier to suggest appropriate levels:

// Returns suggested level based on keywords
classifyLogLevel("Database connection failed");  // 'error'
classifyLogLevel("Retry attempt 3 of 5");        // 'warn'
classifyLogLevel("User logged in");              // 'info'
classifyLogLevel("Cache hit for key xyz");       // 'debug'

Step 7: Enforce Logger Interface

The mock logger implements a strict interface. Your production logger should match:

interface StructuredLogger {
  debug(message: string, context?: Record<string, unknown>): void;
  info(message: string, context?: Record<string, unknown>): void;
  warn(message: string, context?: Record<string, unknown>): void;
  error(message: string, error?: Error, context?: Record<string, unknown>): void;
}

Note: error() has a different signature — it accepts an optional Error instance as the second argument for stack trace capture.


Common Misclassifications

Log MessageWrong LevelCorrect LevelWhy
Cold start recoverywarninfoRecovery is expected, not degradation
Stale flush skipwarndebugExpected race condition, not actionable
Periodic heartbeat tickinfodebugRoutine operation, not state change
User authentication failedinfoerrorSecurity event requiring investigation
Config validation warningdebugwarnHuman should know about config issues

Violation Rules

missing_error_log_assertion

Error paths MUST have log assertions verifying correct error logging with context. Severity: must-fail

happy_path_logs_error

Happy paths MUST NOT produce warn or error logs. Use assertNoLogsAbove(logger, 'info'). Severity: must-fail

log_level_misclassification

Log levels MUST follow the policy. Routine operations at warn/error = alert fatigue. Severity: should-fail

missing_context_fields

Error logs MUST include context fields for debugging (component, userId, requestId, etc.). Severity: should-fail

console_spy_instead_of_mock

DO NOT spy on console.* — use a proper mock logger interface. Severity: must-fail


Companion Skills

This skill provides testing utilities for structured logging, not logging architecture guidance. For broader methodology:

  • Search logging or observability on skills.sh for production logging architecture, wide events, and OpenTelemetry integration
  • Error paths tested here often originate from resilience scenarios — use fault-injection-testing for circuit breaker, retry policy, and queue preservation testing
  • State machine transitions should log state changes at correct levels — use model-based-testing for systematic transition matrix coverage

Quick Reference

AssertionWhenExample
assertLogEntryVerify specific logassertLogEntry(logger, 'error', 'Failed', {component: 'X'})
assertNoLogsAboveHappy path validationassertNoLogsAbove(logger, 'info')
assertHasLogLevelVerify level existsassertHasLogLevel(logger, 'error')
assertErrorLoggedVerify Error instanceassertErrorLogged(logger, 'Failed', {name: 'TypeError'})
classifyLogLevelSuggest correct levelclassifyLogLevel("Connection timeout") → 'warn'

See patterns.md for correlation field patterns, log level migration guides, and framework integration.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.56%
按下载量换算34

Claude

28.81%
按下载量换算27

Cursor

17.11%
按下载量换算16

Gemini CLI

8.87%
按下载量换算8

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

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来源信息

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