Agent skill

Maintainx Observability

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Implement comprehensive observability for MaintainX integrations.

MITAuto-check passedDevOps & Cloud

Install Maintainx Observability

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill maintainx-observability -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace maintainx-observability --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/maintainx-observability .claude/skills/maintainx-observability && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
maintainx-observability
GitHub stars
2.8k
Token cost
~2.1k tokens
SKILL.md length
176 words
Files
2 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Implement comprehensive observability for MaintainX integrations.

  • Works in 5 steps: Prometheus Metrics → Instrumented API Client → Structured Logging → …
  • Setting up monitoring
  • SKILL.md covers Overview, Prerequisites, Instructions and Output, plus 4 more sections
  • Reaches api.getmaintainx.com

What it does

Maintainx Observability is an agent skill from jeremylongshore/tons-of-skills-marketplace. Implement comprehensive observability for MaintainX integrations. Use when setting up monitoring, logging, tracing, and alerting for MaintainX API integrations. Trigger with phrases like "maintainx monitoring", "maintainx logging", "maintainx metrics", "maintainx observability", "maintainx alerts".

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/implementation-guide.md`). Compatibility notes: Designed for Claude Code

It sits in DevOps & Cloud, covering Observability, Monitoring and alerting and Third-party API integration. It works with Prometheus. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Setting up monitoring
  • Alerting for MaintainX API integrations
  • With phrases like maintainx monitoring
  • Maintainx logging

Example prompts

  • “maintainx monitoring”
  • “maintainx logging”
  • “maintainx metrics”
  • “/maintainx-observability”

Requirements

  • Node.js
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash(npm:*)

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Prometheus Metrics
  2. Instrumented API Client
  3. Structured Logging
  4. Health and Metrics Endpoints
  5. Alerting Rules (Prometheus)

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash(npm:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are typescript and yaml).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • api.getmaintainx.com

    Also links to:

    • github.com
    • prometheus.io

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Maintainx Observability loads about 2.1k tokens when it runs, and up to ~6.2k if it reads all its reference files. Until then it costs about 81 tokens; SKILL.md has 176 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~81
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 176 words, ~2,075 tokens.

Download SKILL.mdSave it as .claude/skills/maintainx-observability/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
maintainx-observability
description
Implement comprehensive observability for MaintainX integrations. Use when setting up monitoring, logging, tracing, and alerting for MaintainX API integrations. Trigger with phrases like "maintainx monitoring", "maintainx logging", "maintainx metrics", "maintainx observability", "maintainx alerts".
allowed-tools
Read, Write, Edit, Bash(npm:*)
compatibility
Designed for Claude Code
version
1.11.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, maintainx, api, monitoring, observability

MaintainX Observability

Overview

Implement metrics, structured logging, and alerting for MaintainX integrations to ensure reliability and rapid issue detection.

Prerequisites

  • MaintainX integration deployed
  • Node.js 18+
  • Monitoring platform (Prometheus/Grafana, Datadog, or CloudWatch)

Instructions

Step 1: Prometheus Metrics
typescript
// src/observability/metrics.ts
import { Counter, Histogram, Gauge, Registry } from 'prom-client';

const register = new Registry();

export const metrics = {
  apiRequests: new Counter({
    name: 'maintainx_api_requests_total',
    help: 'Total MaintainX API requests',
    labelNames: ['method', 'endpoint', 'status'],
    registers: [register],
  }),

  apiLatency: new Histogram({
    name: 'maintainx_api_latency_seconds',
    help: 'MaintainX API request latency',
    labelNames: ['method', 'endpoint'],
    buckets: [0.1, 0.25, 0.5, 1, 2.5, 5, 10],
    registers: [register],
  }),

  rateLimitHits: new Counter({
    name: 'maintainx_rate_limit_hits_total',
    help: 'Times rate limited by MaintainX API',
    registers: [register],
  }),

  workOrdersProcessed: new Counter({
    name: 'maintainx_work_orders_processed_total',
    help: 'Work orders processed',
    labelNames: ['action', 'status'],
    registers: [register],
  }),

  syncLag: new Gauge({
    name: 'maintainx_sync_lag_seconds',
    help: 'Seconds since last successful sync',
    registers: [register],
  }),
};

export { register };
Step 2: Instrumented API Client
typescript
// src/observability/instrumented-client.ts
import axios, { AxiosInstance } from 'axios';
import { metrics } from './metrics';

export function createInstrumentedClient(apiKey: string): AxiosInstance {
  const client = axios.create({
    baseURL: 'https://api.getmaintainx.com/v1',
    headers: { Authorization: `Bearer ${apiKey}`, 'Content-Type': 'application/json' },
    timeout: 30_000,
  });

  client.interceptors.request.use((config) => {
    (config as any).__startTime = process.hrtime.bigint();
    return config;
  });

  client.interceptors.response.use(
    (response) => {
      const elapsed = Number(process.hrtime.bigint() - (response.config as any).__startTime) / 1e9;
      const endpoint = response.config.url?.split('?')[0] || 'unknown';

      metrics.apiRequests.inc({
        method: response.config.method?.toUpperCase() || 'GET',
        endpoint,
        status: String(response.status),
      });
      metrics.apiLatency.observe(
        { method: response.config.method?.toUpperCase() || 'GET', endpoint },
        elapsed,
      );
      return response;
    },
    (error) => {
      const status = error.response?.status || 0;
      const endpoint = error.config?.url?.split('?')[0] || 'unknown';

      metrics.apiRequests.inc({
        method: error.config?.method?.toUpperCase() || 'GET',
        endpoint,
        status: String(status),
      });

      if (status === 429) {
        metrics.rateLimitHits.inc();
      }
      throw error;
    },
  );

  return client;
}
Step 3: Structured Logging
typescript
// src/observability/logger.ts

type LogLevel = 'debug' | 'info' | 'warn' | 'error';

interface LogEntry {
  level: LogLevel;
  message: string;
  service: string;
  timestamp: string;
  [key: string]: any;
}

class StructuredLogger {
  private service: string;

  constructor(service: string) {
    this.service = service;
  }

  private log(level: LogLevel, message: string, data?: Record<string, any>) {
    const entry: LogEntry = {
      level,
      message,
      service: this.service,
      timestamp: new Date().toISOString(),
      ...data,
    };
    // JSON output for log aggregation (ELK, CloudWatch, Datadog)
    console.log(JSON.stringify(entry));
  }

  info(message: string, data?: Record<string, any>) { this.log('info', message, data); }
  warn(message: string, data?: Record<string, any>) { this.log('warn', message, data); }
  error(message: string, data?: Record<string, any>) { this.log('error', message, data); }
  debug(message: string, data?: Record<string, any>) { this.log('debug', message, data); }
}

export const logger = new StructuredLogger('maintainx-integration');

// Usage
logger.info('Work order created', { workOrderId: 12345, priority: 'HIGH' });
logger.error('API call failed', { endpoint: '/workorders', status: 500, retryCount: 2 });
Step 4: Health and Metrics Endpoints
typescript
// src/observability/server.ts
import express from 'express';
import { register, metrics } from './metrics';

const app = express();

// Prometheus scrape endpoint
app.get('/metrics', async (req, res) => {
  res.set('Content-Type', register.contentType);
  res.end(await register.metrics());
});

// Health check with metrics
app.get('/health', async (req, res) => {
  const health = {
    status: 'healthy',
    uptime: process.uptime(),
    metrics: {
      totalRequests: await metrics.apiRequests.get(),
      rateLimitHits: await metrics.rateLimitHits.get(),
      syncLagSeconds: (await metrics.syncLag.get()).values[0]?.value || 0,
    },
  };
  res.json(health);
});

app.listen(9090, () => logger.info('Metrics server on :9090'));
Step 5: Alerting Rules (Prometheus)
yaml
# prometheus/alerts.yml
groups:
  - name: maintainx
    rules:
      - alert: MaintainXHighErrorRate
        expr: rate(maintainx_api_requests_total{status=~"5.."}[5m]) > 0.1
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: "MaintainX API error rate > 10%"

      - alert: MaintainXHighLatency
        expr: histogram_quantile(0.95, rate(maintainx_api_latency_seconds_bucket[5m])) > 5
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "MaintainX API p95 latency > 5s"

      - alert: MaintainXRateLimited
        expr: rate(maintainx_rate_limit_hits_total[5m]) > 0
        for: 1m
        labels:
          severity: warning
        annotations:
          summary: "MaintainX API rate limiting detected"

      - alert: MaintainXSyncStale
        expr: maintainx_sync_lag_seconds > 900
        for: 5m
        labels:
          severity: critical
        annotations:
          summary: "MaintainX sync lag > 15 minutes"

Output

  • Prometheus metrics (request count, latency histogram, rate limit counter, sync lag gauge)
  • Instrumented axios client automatically recording metrics on every API call
  • Structured JSON logging for all operations
  • /metrics endpoint for Prometheus scraping
  • Alerting rules for error rate, latency, rate limits, and sync staleness

Error Handling

IssueCauseSolution
Metrics endpoint 500prom-client not initializedEnsure Registry is created before metrics
Missing labelsMetric name mismatchCheck labelNames match inc()/observe() calls
Log volume too highDebug logging in productionSet LOG_LEVEL=info in production
Stale sync alertSync job stoppedCheck cron schedule, restart sync process

Resources

Next Steps

For incident response, see maintainx-incident-runbook.

Examples

Datadog integration using DogStatsD:

typescript
import StatsD from 'hot-shots';

const dogstatsd = new StatsD({ prefix: 'maintainx.' });

// Record API call
dogstatsd.increment('api.requests', 1, { endpoint: '/workorders', status: '200' });
dogstatsd.histogram('api.latency', 0.45, { endpoint: '/workorders' });

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in skills/.curated/maintainx-observability of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/implementation-guide.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

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Maintainx Observability compared with similar skills
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WizTelemetry Platform Servicekubesphere/kubesphere17k—~1.8kAutomated safety check: PassCustom licence
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Alicloud Acs Agent Sandboxcinience/alicloud-skills397—~2.7kAutomated safety check: PassMIT
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Works with

Categories

Questions about Maintainx Observability

What does Maintainx Observability do?

Implement comprehensive observability for MaintainX integrations. Maintainx Observability is an agent skill from jeremylongshore/tons-of-skills-marketplace. Implement comprehensive observability for MaintainX integrations.

When should I use Maintainx Observability?

Maintainx Observability fits situations like: setting up monitoring; alerting for MaintainX API integrations; with phrases like maintainx monitoring; maintainx logging.

How do I install Maintainx Observability in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill maintainx-observability -a claude-code`. Or copy the skill folder (skills/.curated/maintainx-observability in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/maintainx-observability in your project. Claude Code loads it when a task matches its description.

How do I install Maintainx Observability in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill maintainx-observability -a codex`. Or copy the skill folder (skills/.curated/maintainx-observability in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/maintainx-observability in your project. Codex loads it when a task matches its description.

Can I use Maintainx Observability in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill maintainx-observability -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/maintainx-observability, .gemini/skills/maintainx-observability, .github/skills/maintainx-observability and .opencode/skills/maintainx-observability in your project.

What does Maintainx Observability need to run?

SKILL.md names no scripts, command-line tools or credentials: Maintainx Observability is instructions for the agent only. Our summary lists: Node.js. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash(npm:*). Compatibility (from SKILL.md): Designed for Claude Code.

Does Maintainx Observability access the network?

SKILL.md names 3 domains. In commands or code: api.getmaintainx.com; the agent is likely to contact it when it follows the instructions. As links in the text: github.com and prometheus.io. This is read from the text; nothing was executed.

Is Maintainx Observability safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Maintainx Observability use?

Maintainx Observability is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Maintainx Observability use?

About 2.1k tokens (SKILL.md is roughly 8.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.1k tokens, read only when the agent opens those files.

What are the alternatives to Maintainx Observability?

Skills that share tags, products or a category with Maintainx Observability: Happy Infra Metrics and Grafana (slopus/happy, 24k stars), WizTelemetry Platform Service (kubesphere/kubesphere, 17k stars), Redis Observability (redis/agent-skills, 166 stars) and Alicloud Acs Agent Sandbox (cinience/alicloud-skills, 397 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Maintainx Observability?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.