maple-onboarding-style

Standardize OpenTelemetry instrumentation across Maple services with native APIs and semantic conventions.

1.6k|107|Updated Feb 15, 2026
One-click install
npx skills add https://github.com/MapleTechLabs/maple --skill maple-onboarding-style-mapletechlabs
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: maple-onboarding-style
Source: https://github.com/MapleTechLabs/maple/tree/main/skills/maple-onboarding-style
Command: npx skills add https://github.com/MapleTechLabs/maple --skill maple-onboarding-style-mapletechlabs

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates inconsistent OpenTelemetry implementation across Maple services, which causes missing telemetry data, poor trace correlation, and increased debugging time for production issues.

Core Features & Use Cases

  • Native OTel API Enforcement: Requires use of official OpenTelemetry APIs and the @maple/otel-helpers withSpan helper for bounded business spans, avoiding custom telemetry wrappers.
  • Standardized Conventions: Defines consistent span naming, resource attribute formatting (including VCS metadata), and LLM telemetry patterns to ensure all Maple services emit compatible observability data.
  • Smoke Check Guidance: Provides instructions for validating OTel bootstrap loads correctly, exercising instrumented spans/logs/metrics to catch setup errors early.
  • Use Case: A team building a new Maple LLM-powered chat service uses this Skill to implement compliant telemetry that integrates seamlessly with Maple's observability platform, eliminating gaps in trace coverage and reducing incident response time.

Quick Start

Use the maple-onboarding-style skill to implement standardized OpenTelemetry instrumentation for your new Maple service, including proper span naming, VCS resource attributes, and LLM metrics setup.

Frequently Asked Questions about maple-onboarding-style

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I standardize OpenTelemetry instrumentation across microservices?

Standardize OpenTelemetry instrumentation by enforcing native OTel APIs and the @maple/otel-helpers withSpan helper for bounded business spans, ensuring consistent observability data and eliminating trace correlation gaps across Maple microservices.

How do I configure VCS resource attributes for OpenTelemetry traces?

Configure VCS resource attributes for OpenTelemetry traces by applying standardized semantic convention attribute formatting, which binds version control metadata to your telemetry data for better trace correlation and debugging context.

What is the best way to implement LLM telemetry for observability?

Implement LLM telemetry by applying standardized LLM metrics collection patterns alongside native OpenTelemetry APIs, ensuring your LLM-powered applications emit compatible observability data and capture accurate performance metrics.

Can I use custom telemetry wrappers instead of native OpenTelemetry APIs?

You should avoid custom telemetry wrappers; this standardization enforces official OpenTelemetry APIs and the @maple/otel-helpers withSpan helper to prevent inconsistent observability data and ensure proper trace correlation.

How do I validate OpenTelemetry bootstrap loads correctly?

Validate OpenTelemetry bootstrap loads by running durable smoke checks that exercise instrumented spans, logs, and metrics, catching setup errors early before they cause missing telemetry data in production.

Why does my OpenTelemetry setup produce inconsistent observability data?

Inconsistent observability data usually stems from non-standard span naming and missing telemetry coverage; standardizing OTel semantic conventions and resource attribute formatting eliminates these gaps and improves trace correlation.