183 Java Observability Tracing Opentelemetry

Community

jabrena

183-java-observability-tracing-opentelemetry

Use when you need to implement or improve distributed tracing with OpenTelemetry in Java — including trace/span modeling, context propagation, semantic conventions, span attributes/events/status, sampling strategy, baggage usage, privacy safeguards, and backend integration with OTLP collectors. This should trigger for requests such as Improve tracing; Apply OpenTelemetry tracing; Add distributed tracing; Refactor tracing instrumentation; Instrument Java services with OpenTelemetry spans. Part of Plinth Toolkit

Overview

Publisher	jabrena
Repository	`plinth`
Skill name	`183-java-observability-tracing-opentelemetry`
Stars	455
Forks	95
Bundled files	1
License	Apache-2.0
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by jabrena on GitHub. Read the source before you install it.

Installation

Install the 183 Java Observability Tracing Opentelemetry AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/jabrena/plinth/tree/main/skills/183-java-observability-tracing-opentelemetry
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/jabrena/plinth/tree/main/skills/183-java-observability-tracing-opentelemetry

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/jabrena/plinth.git /tmp/plinth
mkdir -p .claude/skills
cp -r /tmp/plinth/skills/183-java-observability-tracing-opentelemetry .claude/skills/183-java-observability-tracing-opentelemetry

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 183 Java Observability Tracing Opentelemetry in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads 183 Java Observability Tracing Opentelemetry on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so 183 Java Observability Tracing Opentelemetry is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Java Distributed Tracing with OpenTelemetry

Implement robust distributed tracing in Java with OpenTelemetry by modeling meaningful spans, preserving context propagation, and instrumenting critical business and infrastructure paths with low-overhead, privacy-safe telemetry.

What is covered in this Skill?

OpenTelemetry tracing fundamentals for Java services
Span design: boundaries, parent/child relationships, and operation naming
Context propagation across HTTP, messaging, async tasks, and thread boundaries
Semantic conventions and stable attribute naming
Error/status/event recording best practices
Sampling strategy and performance/cost trade-offs
Privacy and security controls for trace attributes
Testing and verification of trace propagation and span correctness

Scope: Distributed tracing quality in application and integration layers, focused on diagnosability, consistency, and operational safety.

Constraints

Tracing instrumentation must preserve context correctly and avoid leaking sensitive data. Over-instrumentation and high-cardinality attributes can harm cost and signal quality.

PROPAGATION FIRST: Ensure context propagation across all sync/async boundaries before adding extra span detail
NO SENSITIVE DATA: Never store secrets, credentials, tokens, raw payloads, or PII in span attributes/events
LOW CARDINALITY ATTRIBUTES: Avoid unbounded values in attributes that are used for aggregation/search
VERIFY: Run ./mvnw clean verify or mvn clean verify after applying tracing changes

When to use this skill

Improve tracing
Apply OpenTelemetry tracing
Add distributed tracing
Refactor tracing instrumentation
Instrument Java services with OpenTelemetry spans

Workflow

Define trace model and critical flows

Identify high-value request and async flows, define operation boundaries, and choose span names/attributes aligned with semantic conventions.

Instrument and propagate context

Add OpenTelemetry spans to key boundaries and ensure trace context is propagated across HTTP clients/servers, messaging, and executor-based async work.

Harden span data and sampling

Record status/errors/events consistently, remove sensitive data, control attribute cardinality, and configure sampling/exporters according to environment needs.

Validate traces end-to-end

Verify parent-child relationships, propagation continuity, and backend visibility through tests and runtime checks.

Reference

For detailed guidance, examples, and constraints, see references/183-java-observability-tracing-opentelemetry.md.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

references/183-java-observability-tracing-opentelemetry.md14 KB

Frequently asked questions

What does the 183 Java Observability Tracing Opentelemetry AI skill do?

Why use 183 Java Observability Tracing Opentelemetry on TypingMind?

Because you install it once and use it with any model. 183 Java Observability Tracing Opentelemetry is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install 183 Java Observability Tracing Opentelemetry in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jabrena/plinth/tree/main/skills/183-java-observability-tracing-opentelemetry. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use 183 Java Observability Tracing Opentelemetry?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with 183 Java Observability Tracing Opentelemetry?

As many as you like. As long as a model supports skills, you can use 183 Java Observability Tracing Opentelemetry with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 183 Java Observability Tracing Opentelemetry AI skill free?

Yes. It is published on GitHub by jabrena under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Java Distributed Tracing with OpenTelemetry

Constraints

When to use this skill

Workflow

Reference

Bundled files

Frequently asked questions

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