Guides an AI coding agent in configuring and deploying the OpenTelemetry Collector, the service that receives, processes and forwards application monitoring data. It covers data pipelines, deployment methods, sampling and performance tuning.
WHEN TO USE
SCOPE
USE FOR
Write a Collector pipeline that receives OTLP or Prometheus data and sends it to Dash0.
Fix a Collector config that keeps running out of memory or dropping telemetry.
Deploy the Collector to Kubernetes using Helm, an Operator, or raw manifests.
Cut the volume of traces you store without losing the ones showing errors or slow requests.
Turn raw traces into request-rate, error-rate, and duration metrics.
Build a smaller, custom Collector binary with only the components you actually use.
This is a saved copy of the skill's SKILL.md instructions. It may differ from the upstream file or the version you install.
OpenTelemetry Collector configuration guide
Expert guidance for configuring and deploying the OpenTelemetry Collector to receive, process, and export telemetry.
Custom distributions — building a stripped-down Collector binary with OCB
Key principles
Processor ordering matters.
Place memory_limiter first in every pipeline.
Use the exporter's sending_queue with file_storage instead of the batch processor.
Incorrect ordering causes memory exhaustion or data loss.
One pipeline per signal type.
Define separate pipelines for traces, metrics, and logs.
Mixing signals in a single pipeline breaks processing and causes runtime errors.
Every declared component must appear in a pipeline.
The Collector rejects configurations that declare receivers, processors, or exporters not referenced by any pipeline.
Consistent resource enrichment across pipelines.
Apply processors that enrich resource attributes like resourcedetection and k8sattributes to every signal pipeline (traces, metrics, and logs), not just one.
If one pipeline enriches telemetry with k8s.namespace.name or host.name but another does not, correlation between signals is compromised by incomplete metadata.
Memory safety is non-negotiable.
Always configure memory_limiter in production.
Without it, a burst of telemetry can cause the Collector to OOM and crash.
Quick start
Minimal working configuration: OTLP receiver → memory limiter → OTLP/gRPC exporter to Dash0.
See exporters for full authentication and queue configuration, and processors for adding resource detection.
Configuration workflow
Write config — define receivers, processors, and exporters; wire them in service.pipelines.
Validate locally — run otelcol validate --config=config.yaml to catch structural errors before deployment.
Deploy — choose a deployment method from the deployment rule (Helm, Operator, raw manifests, or Docker Compose).
Verify — add the debug exporter to a pipeline temporarily and inspect stdout to confirm telemetry is flowing; then remove it before going to production.
The Collector needs somewhere to forward data. The skill's exporter examples use a Dash0 endpoint and a Dash0 auth token read from an environment variable (DASH0_TOKEN in the quick-start, DASH0_AUTH_TOKEN in the exporter rules). With another OTLP-compatible backend, use that backend's endpoint and credentials instead.
Listed as free
Connected services may require an account or charge fees.
Setup details
The README mentions source builds, cloning, containers, hosting, OAuth, service accounts, or cloud projects.
Run this outside your AI tool, using Node.js 22.20.0 or newer. Skills CLI 1.7.2 skips skill selection; prompts cancel installation without an interactive terminal. If choosing Project when asked about installation scope, open your project's folder before running this.
Install checklist
Check selected tools if a picker appears; Claude Code may be unchecked under Additional agents. ↑/↓ moves, Space toggles selections, Enter confirms.
Without a tool picker, check Installing to: for your intended tool. Stop if it names a different tool.
If asked, choose Symlink (Recommended) for shared files or Copy to all agents for separate copies; review the summary before confirming installation.
Install the find-skills skill? defaults to Yes, adding another skill for all projects. Choose No if you don't want that extra installation.
Skills CLI 1.7.2 sends install data to skills.sh by default, including the source, skill names, target tools and file details; GitHub sources are reported only when GitHub confirms the repository is public, while other remote sources can also be reported. Confirmed-public GitHub sources also trigger a security-audit request. Before installing, set the environment variable DO_NOT_TRACK=1 or DISABLE_TELEMETRY=1 to disable both.
After installing for Claude Code, open it in the installation project if you chose Project; Global makes the skill available across projects on this computer. Once Claude Code loads the skill, its description helps Claude decide when to use it.
If installation created a top-level skills folder that did not exist when your Claude Code session started, run /reload-skills in that session. Run it again after later changes in that folder.
Install the whole plugin
This route installs the Dash0 Agent Skills plugin package selected for your AI tool.
By tool
Packages & runtimes
Add the marketplace, then install the plugin
Enter both lines in a Claude Code session. They add Dash0’s marketplace and open the four-skill plugin for installation; choose where to enable it in the install panel.
Install checklist
Have Claude Code available to enter these session commands.
Choose dash0-agent-skills; Dash0’s marketplace also lists a different plugin named dash0-agent-plugin.
Choose user, project or local scope according to where you want the plugin enabled.
Read the install summary and follow any reload instruction. Check the / menu for the plugin’s skills.
Your agent can select relevant skills automatically. To choose one explicitly, use /plugin-name:skill-name for plugin skills; direct skill installations use /skill-name.
Clone Dash0’s repository
Run this terminal command to copy Dash0’s four-skill repository into ~/.agents/skills/dash0-agent-skills.
Install checklist
Have Git installed to clone the repository.
If the destination already contains this repository, reuse it rather than cloning into the same folder again.
Open /skills and check for the four skill names. Your agent can select a matching skill automatically; use /skills or $ to choose explicitly.
In a Vercel Sandbox, Codex CLI 0.162.1 listed all four skills through codex debug prompt-input without login; removing this clone removed them from the list.
Install from Dash0’s GitHub repository
Enter Dash0’s command in an interactive GitHub Copilot CLI session. It requests a direct plugin installation from the repository; GitHub documents direct installations under ~/.copilot/installed-plugins/_direct/.
Install checklist
Use GitHub Copilot CLI for this session command; other Copilot interfaces have their own installation controls.
Copilot CLI 1.0.95 warns that direct repository installs are deprecated; a future release will accept only plugin@marketplace installs.
Use copilot skill list to check for the four skills. Your agent can load relevant skills automatically.
In a Vercel Sandbox with no Dash0 clones active, Copilot CLI 1.0.95 installed and listed four skills without login through terminal subcommands; session slash commands were untested.
Clone into your local skills folder
Dash0 documents this terminal command to copy its four-skill repository into ~/.cursor/skills/dash0-agent-skills. Cursor lists ~/.cursor/skills as a local user skills location.
Install checklist
Have Git installed to clone the repository.
This folder stays on your machine. For Cloud Agents, sync personal Cursor skills or use project skills.
Discovery of the four nested skills through this clone route has not been tested in Cursor.
In Agent chat, type / and check for the four skill names before relying on them.
Your agent selects relevant skills from context. Selecting a skill through / attaches it to that message.
Install the Gemini CLI extension
Run this command in a terminal. It installs Dash0’s repository as a Gemini CLI extension containing four skills under ~/.gemini/extensions/dash0-agent-skills.
Install checklist
Have Gemini CLI available to run the extension installer.
Have Git installed; Gemini CLI requires it for extensions installed from GitHub.
In our Vercel Sandbox run, Gemini CLI 0.63.0 prompted for workspace trust and skill approval in an initially untrusted workspace; review installation prompts.
Restart your Gemini CLI session for the extension changes to take effect.
Use /skills list to inspect discovered skills. When your agent proposes activation for a matching task, review its skill-directory access prompt before approving.
Clone into the local skills folder
Run this terminal command to copy Dash0’s four-skill repository into ~/.openclaw/skills/dash0-agent-skills.
Install checklist
Have Git installed to clone the repository.
Check your OpenClaw state directory; the command targets ~/.openclaw, while managed skills follow the configured state directory.
In the Control UI, type $ and check for the four skills. Your agent can select them automatically; use $skill-name to reference one explicitly.
In a Vercel Sandbox, OpenClaw 2026.6.35 listed four skills through openclaw skills list --json with only this OpenClaw clone active; invocation was untested.
Clone Dash0’s repository
Run this terminal command to copy Dash0’s four-skill repository into ~/.agents/skills/dash0-agent-skills.
Install checklist
Have Git installed to clone the repository.
If you already cloned this repository for Codex, reuse it: both panels target the same directory.
Your agent can select and load these skills when relevant. Their metadata does not enable /name commands in OpenCode.
In a Vercel Sandbox, OpenCode 1.19.0 listed four skills through opencode debug skill without login; removing this clone removed them from the list. Invocation was untested.
Install into your repository
Run this command in a terminal inside your Git repository. It installs Dash0’s four-skill registry plugin under .tessl/plugins/dash0/agent-skills and links skills into detected agents’ directories.
Install checklist
Install Tessl CLI first; native, Homebrew and winget installers are available. npm installation is deprecated.
In our Vercel Sandbox run, Tessl CLI 0.114.0 initialized an empty Git repository without tessl.json, wrote AGENTS.md and configured four detected agents’ Tessl MCP connections.
Review these project and agent configuration changes before installing.
tessl install dash0/agent-skills
Installation and loading
Tessl records the plugin reference in tessl.json.
Tessl says your agent loads relevant skills from your task, files and conversation context, without explicit invocation. Loading through these links was not tested.
Good to know
Tessl’s --global option installs plugins under ~/.tessl/plugins/ for use across repositories.
That sandbox installation completed without login.
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