Otel Semantic Conventions logo

Otel Semantic Conventions

Organization
dash0hq
otel-semantic-conventions

OpenTelemetry Semantic Conventions expert. Use when selecting, applying, or reviewing telemetry attributes. Triggers on tasks involving attribute selection, semantic convention compliance, attribute migration, or custom attribute decisions. Covers the attribute registry, naming patterns, attribute placement, and versioning. For span names, span kinds, and span status codes, see the otel-instrumentation skill.

Overview

Publisherdash0hq
Repositoryagent-skills
Skill nameotel-semantic-conventions
Stars
98
Forks
16
Bundled files
3
LicenseApache-2.0
Links
  • 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.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by dash0hq on GitHub. Read the source before you install it.

Installation

Install the Otel Semantic Conventions AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/dash0hq/agent-skills/tree/main/skills/otel-semantic-conventions
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

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/dash0hq/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/skills/otel-semantic-conventions .claude/skills/otel-semantic-conventions
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Otel Semantic Conventions 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 Otel Semantic Conventions 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 Otel Semantic Conventions 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.

OpenTelemetry Semantic Conventions

This skill governs correct selection, placement, and validation of telemetry attributes and metric instruments according to the OpenTelemetry Semantic Conventions specification. For span naming, span kinds, and span status codes, see the otel-instrumentation skill.

The Attribute Registry is the single source of truth for all defined attributes.

Rules

RuleDescriptionUse Case
attributesAttribute registry, selection, placement, common attributes by domainChoosing or reviewing attributes; HTTP/DB/messaging/RPC attributes; attribute placement (resource vs span)
versioningSemconv versioning, stability, migrationSemconv version migration
dash0Dash0 derived attributes and feature dependenciesDash0 derived attributes

Official documentation

How to select the right attribute

  1. Search the registry first — Look up the concept in the Attribute Registry. Use the standard name if it exists (e.g., prefer http.request.method over a custom custom.http.verb). Custom names fragment querying and break tooling — only create a custom attribute when no registry entry covers the concept.
  2. Check stability — Prefer stable attributes; note any experimental attributes that may change. See versioning.
  3. Place at the correct level — Resource attributes describe the entity producing telemetry; span/log attributes describe the individual operation. Do not duplicate across levels. Once an attribute is at a given level, keep it there consistently across all services.
  4. Verify cardinality — Metric attribute values must be low-cardinality (bounded set). Variable data (user IDs, request paths with parameters) belongs in span attributes, not metric attributes.
  5. Custom attribute as last resort — Only create a custom attribute if no registry entry covers the concept. Document the decision and follow the org.namespace.attribute_name naming pattern.

Example: correct vs incorrect attribute selection

# Correct — uses registry attribute for HTTP method
span.set_attribute("http.request.method", "GET")

# Incorrect — invents a custom attribute for a concept already in the registry
span.set_attribute("custom.http.verb", "GET")

Example: resource vs span attribute placement

# Correct — service identity is a resource attribute
resource = Resource({"service.name": "checkout-service", "service.version": "2.1.0"})

# Correct — operation-specific data is a span attribute
span.set_attribute("http.request.method", "POST")
span.set_attribute("http.response.status_code", 201)

# Incorrect — placing a resource-level attribute on every span
span.set_attribute("service.name", "checkout-service")  # belongs on the resource

Example: cardinality violation in metric attributes

# Correct — metric attribute uses a bounded, low-cardinality value
histogram.record(duration_ms, {"http.request.method": "GET", "http.response.status_code": 200})

# Incorrect — unbounded values as metric attributes explode storage and query cost
histogram.record(duration_ms, {"user.id": "u-839201", "url.path": "/orders/839201"})
# Fix: move high-cardinality values to span attributes instead
span.set_attribute("user.id", "u-839201")
span.set_attribute("url.path", "/orders/839201")

Bundled files

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

Frequently asked questions

What does the Otel Semantic Conventions AI skill do?

OpenTelemetry Semantic Conventions expert. Use when selecting, applying, or reviewing telemetry attributes. Triggers on tasks involving attribute selection, semantic convention compliance, attribute migration, or custom attribute decisions. Covers the attribute registry, naming patterns, attribute placement, and versioning. For span names, span kinds, and span status codes, see the otel-instrumentation skill.

Why use Otel Semantic Conventions on TypingMind?

Because you install it once and use it with any model. Otel Semantic Conventions 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 Otel Semantic Conventions in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dash0hq/agent-skills/tree/main/skills/otel-semantic-conventions. 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 Otel Semantic Conventions?

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 Otel Semantic Conventions?

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

Is the Otel Semantic Conventions AI skill free?

Yes. It is published on GitHub by dash0hq 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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