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evernote-observabilityEvernote 可观测性

Agent Skill

evernote-observability 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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

523

周安装

22

GitHub Stars

2,138

下载量

183
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:evernote-observability(Evernote 可观测性)
来源仓库:https://github.com/jeremylongshore/claude-code-plugins-plus-skills
仓库路径:skills/evernote-observability
安装命令:
npx skills add https://github.com/jeremylongshore/claude-code-plugins-plus-skills --skill evernote-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。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/jeremylongshore/claude-code-plugins-plus-skills --skill evernote-observability

简介

evernote-observability 建立集成系统的可观测性体系,包含 Prometheus 指标、结构化日志与 OpenTelemetry 追踪。

  • 适用于生产环境中监控 API 调用频次、延迟与错误率等关键指标。
  • 提供健康检查端点、告警规则模板与日志聚合集成方案。
  • 使用前需部署 Prometheus、日志收集器与告警系统(如 PagerDuty 或 Slack Webhook)。
  • 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

Evernote Observability

Overview

Comprehensive observability setup for Evernote integrations: Prometheus metrics for API call tracking, structured JSON logging, OpenTelemetry tracing, health check endpoints, and alerting rules.

Prerequisites

  • Monitoring infrastructure (Prometheus, Datadog, or CloudWatch)
  • Log aggregation (ELK, Loki, or CloudWatch Logs)
  • Alerting system (PagerDuty, Opsgenie, or Slack webhooks)

Instructions

Step 1: Metrics Collection

Track key metrics with Prometheus counters and histograms: evernote_api_calls_total (by method and status), evernote_api_duration_seconds (latency histogram), evernote_rate_limits_total (rate limit hits), evernote_quota_usage_bytes (upload quota consumption).

const { Counter, Histogram } = require('prom-client');

const apiCalls = new Counter({
  name: 'evernote_api_calls_total',
  help: 'Total Evernote API calls',
  labelNames: ['method', 'status']
});

const apiDuration = new Histogram({
  name: 'evernote_api_duration_seconds',
  help: 'Evernote API call duration',
  labelNames: ['method'],
  buckets: [0.1, 0.5, 1, 2, 5, 10]
});

Step 2: Instrumented Client

Wrap the NoteStore with a Proxy that automatically records metrics for every API call. Increment counters on success/failure, observe latency in histograms, and count rate limit events.

Step 3: Structured Logging

Use JSON-formatted logs with consistent fields: timestamp, level, method, duration, userId (hashed), noteGuid. Redact access tokens from all log output.

function logApiCall(method, duration, error) {
  const entry = {
    timestamp: new Date().toISOString(),
    service: 'evernote-integration',
    method,
    duration_ms: duration,
    status: error ? 'error' : 'success',
    error_code: error?.errorCode
  };
  console.log(JSON.stringify(entry));
}

Step 4: Health and Readiness Endpoints

Implement /health (liveness: is the process running?) and /ready (readiness: can we reach Evernote API?). Include cache connectivity check.

Step 5: Alert Rules

Configure Prometheus alerts: rate limit hits > 5 in 10 minutes, API error rate > 10%, p95 latency > 5 seconds, quota usage > 90%.

# prometheus-alerts.yml
groups:
  - name: evernote
    rules:
      - alert: EvernoteRateLimited
        expr: rate(evernote_rate_limits_total[10m]) > 0.5
        for: 5m
        labels: { severity: warning }
        annotations:
          summary: "Evernote rate limits detected"

For the complete metrics setup, Grafana dashboard JSON, tracing configuration, and alert rules, see Implementation Guide.

Output

  • Prometheus metrics: API calls, latency histogram, rate limits, quota usage
  • Instrumented NoteStore client with automatic metric recording
  • Structured JSON logging with token redaction
  • Health and readiness endpoints
  • Prometheus alert rules for rate limits, errors, and latency

Error Handling

ErrorCauseSolution
Metrics endpoint not scrapedPrometheus target missingAdd service to Prometheus scrape config
Missing trace contextOpenTelemetry not initializedInitialize tracer before creating Evernote client
Log volume too highLogging every API callSample debug logs, always log errors and rate limits
Alert fatigueThresholds too lowTune alert thresholds based on baseline metrics

Resources

Next Steps

For incident handling, see evernote-incident-runbook.

Examples

Grafana dashboard: Display API call rate, p50/p95/p99 latency, error rate, rate limit frequency, and quota usage on a single dashboard. Set time range to last 24 hours.

Rate limit alerting: Alert on-call when rate limit hits exceed 5 per 10-minute window. Include runbook link to evernote-rate-limits in the alert annotation.

适合场景

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能力概览

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能力 2

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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

38.02%
按下载量换算70

Claude

31.51%
按下载量换算58

Cursor

16.97%
按下载量换算31

Gemini CLI

9.52%
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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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