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qa-observability质量保证可观察性

Agent Skill

qa-observability 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

总安装

2,472

周安装

136

GitHub Stars

59

下载量

776
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

3

许可证

MIT

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:qa-observability(质量保证可观察性)
来源仓库:https://github.com/vasilyu1983/ai-agents-public
仓库路径:skills/qa-observability
安装命令:
npx skills add https://github.com/vasilyu1983/ai-agents-public --skill qa-observability
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/vasilyu1983/ai-agents-public --skill qa-observability

简介

qa-observability 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 它支持基于关键词或任务场景的信息匹配,适用于系统可观察性与监控相关的资料准备。
  • 通过安装命令 npx skills add https://github.com/vasilyu1983/ai-agents-public --skill qa-observability 添加技能,具体用法可参考仓库中的 SKILL.md。
  • 安装前请确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

QA Observability and Performance Engineering

Use telemetry (logs, metrics, traces, profiles) as a QA signal and a debugging substrate.

Core references (see data/sources.json): OpenTelemetry, W3C Trace Context, and SLO practices (Google SRE).

Quick Start (Default)

If key context is missing, ask for: critical user journeys, service/dependency inventory, environments (local/staging/prod), current telemetry stack, and current SLO/SLA commitments (if any).

  1. Establish the minimum bar: correlation IDs + structured logs + traces + golden metrics (latency, traffic, errors, saturation).
  2. Verify propagation: confirm traceparent (and your request ID) flow across boundaries end-to-end.
  3. Make failures diagnosable: every test failure captures a trace link (or trace ID) plus the correlated logs.
  4. Define SLIs/SLOs and error budget policy; wire burn-rate alerts (prefer multi-window burn rates).
  5. Produce artifacts: a readiness checklist plus an SLO definition and alert rules (use assets/checklists/template-observability-readiness-checklist.md and assets/monitoring/slo/*).

Default QA stance

  • Treat telemetry as part of acceptance criteria (especially for integration/E2E tests).
  • Require correlation: request_id + trace_id (traceparent) across boundaries.
  • Prefer SLO-based release gating and burn-rate alerting over raw infra thresholds.
  • Budget overhead: sampling, cardinality, retention, and cost are quality constraints.
  • Redact PII/secrets by default (logs and attributes).

Core workflows

  1. Establish the minimum bar (logs + metrics + traces + correlation).
  2. Instrument with OpenTelemetry (auto-instrument first, then add manual spans for key paths).
  3. Verify context propagation across service boundaries (traceparent in/out).
  4. Define SLIs/SLOs and error budget policy; wire burn-rate alerts.
  5. Make failures diagnosable: capture a trace link + key logs on every test failure.
  6. Profile and load test only after telemetry is reliable; validate against baselines.

Quick reference

TaskRecommended defaultNotes
TracingOpenTelemetry + Jaeger/TempoPrefer OTLP exporters via Collector when possible
MetricsPrometheus + GrafanaUse histograms for latency; watch cardinality
LoggingStructured JSON + correlation IDsNever log secrets/PII; redact aggressively
Reliability gatesSLOs + error budgets + burn-rate alertsGate releases on sustained burn/regressions
PerformanceProfiling + load tests + budgetsAdd continuous profiling for intermittent issues
Zero-code visibilityeBPF (OpenTelemetry zero-code) + continuous profiling (Parca/Pyroscope)Use when code changes are not feasible

Navigation

Open these guides when needed:

If the user needs...ReadAlso use
A minimal, production-ready baselinereferences/core-observability-patterns.mdassets/checklists/template-observability-readiness-checklist.md
Node/Python instrumentation setupreferences/opentelemetry-best-practices.mdassets/opentelemetry/nodejs/opentelemetry-nodejs-setup.md, assets/opentelemetry/python/opentelemetry-python-setup.md
Working trace propagation across servicesreferences/distributed-tracing-patterns.mdassets/checklists/template-observability-readiness-checklist.md
SLOs, burn-rate alerts, and release gatesreferences/slo-design-guide.mdassets/monitoring/slo/slo-definition.yaml, assets/monitoring/slo/prometheus-alert-rules.yaml
Profiling/load testing with evidencereferences/performance-profiling-guide.mdassets/load-testing/load-testing-k6.js, assets/load-testing/template-load-test-artillery.yaml
A maturity model and roadmapreferences/observability-maturity-model.mdassets/checklists/template-observability-readiness-checklist.md
What to avoid and how to fix itreferences/anti-patterns-best-practices.mdassets/checklists/template-observability-readiness-checklist.md
Alert design and fatigue reductionreferences/alerting-strategies.mdassets/monitoring/slo/prometheus-alert-rules.yaml
Dashboard hierarchy and layoutreferences/dashboard-design-patterns.mdassets/monitoring/grafana/template-grafana-dashboard-observability.json
Structured logging and cost controlreferences/log-aggregation-patterns.mdassets/observability/template-logging-setup.md

Implementation guides (deep dives):

  • references/core-observability-patterns.md
  • references/opentelemetry-best-practices.md
  • references/distributed-tracing-patterns.md
  • references/slo-design-guide.md
  • references/performance-profiling-guide.md
  • references/observability-maturity-model.md
  • references/anti-patterns-best-practices.md
  • references/alerting-strategies.md
  • references/dashboard-design-patterns.md
  • references/log-aggregation-patterns.md

Templates (copy/paste):

  • assets/checklists/template-observability-readiness-checklist.md
  • assets/opentelemetry/nodejs/opentelemetry-nodejs-setup.md
  • assets/opentelemetry/python/opentelemetry-python-setup.md
  • assets/monitoring/slo/slo-definition.yaml
  • assets/monitoring/slo/prometheus-alert-rules.yaml
  • assets/monitoring/grafana/grafana-dashboard-slo.json
  • assets/monitoring/grafana/template-grafana-dashboard-observability.json
  • assets/load-testing/load-testing-k6.js
  • assets/load-testing/template-load-test-artillery.yaml
  • assets/performance/frontend/template-lighthouse-ci.json
  • assets/performance/backend/template-nodejs-profiling-config.js

Curated sources:

  • data/sources.json

Scope boundaries (handoffs)

  • Pure infrastructure monitoring (Kubernetes, Docker, CI/CD): ../ops-devops-platform/SKILL.md
  • Database query optimization (SQL tuning, indexing): ../data-sql-optimization/SKILL.md
  • Application-level debugging (stack traces, breakpoints): ../qa-debugging/SKILL.md
  • Test strategy design (coverage, test pyramids): ../qa-testing-strategy/SKILL.md
  • Resilience patterns (retries, circuit breakers): ../qa-resilience/SKILL.md
  • Architecture decisions (microservices, event-driven): ../software-architecture-design/SKILL.md

Tool selection notes (2026)

  • Default to OpenTelemetry + OTLP + Collector where possible.
  • Prefer burn-rate alerting against SLOs over alerting on raw infra metrics.
  • Treat sampling, cardinality, and retention as part of quality (not an afterthought).
  • When asked to pick vendors/tools, start from data/sources.json and validate time-sensitive claims with current docs/releases if the environment allows it.

Fact-Checking

  • Use web search/web fetch to verify current external facts, versions, pricing, deadlines, regulations, or platform behavior before final answers.
  • Prefer primary sources; report source links and dates for volatile information.
  • If web access is unavailable, state the limitation and mark guidance as unverified.

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

04

需要参考平台分布和安装热度时

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

补充不同宿主或平台的使用分布数据

能力 5

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

Claude Code

26.32%
按下载量换算204

OpenCode

22.13%
按下载量换算172

Cursor

16.83%
按下载量换算131

Antigravity

12.73%
按下载量换算99

Gemini CLI

7.26%
按下载量换算56

trae

3.29%
按下载量换算26

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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