Dd Apm logo

Dd Apm

Organization
datadog-labs
dd-apm

APM - install, onboard, instrument, enable, set up, configure, traces, services, dependencies, performance analysis. Use for any request involving Datadog APM setup, instrumentation (SSI, ddtrace, agent install), or analysis.

Overview

Publisherdatadog-labs
Repositoryagent-skills
Skill namedd-apm
Stars
172
Forks
28
Bundled files
Instructions only
LicenseMIT
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by datadog-labs on GitHub. Read the source before you install it.

Installation

Install the Dd Apm 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.
  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/datadog-labs/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/dd-apm .claude/skills/dd-apm
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dd Apm 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 Dd Apm 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 Dd Apm 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.

Datadog APM

Distributed tracing, service maps, and performance analysis.

Routing — Read This First

Match the user's request to one of the entries below. Each entry has the same shape: triggers → which sub-skill to load → the anti-pattern to avoid. If a request seems to fit more than one entry, see "Overlap disambiguation". If nothing matches, see "None of the above" at the end.


Kubernetes APM install / instrument / onboard — trigger when the user mentions Kubernetes, K8s, EKS, GKE, AKS, kind, minikube, K3s, helm, DatadogAgent CR, kubectl, SSI on a cluster, pod injection, or init containers.

Immediately read .claude/skills/dd-apm/k8s-ssi/agent-install/SKILL.md now, then .claude/skills/dd-apm/k8s-ssi/enable-ssi/SKILL.md, then .claude/skills/dd-apm/k8s-ssi/verify-ssi/SKILL.md — do not proceed from memory.

Common wrong approaches that LOOK like they work but silently fail:

  • helm install datadog datadog/datadog — the standard chart does NOT support SSI via DatadogAgent CR.
  • Adding ddtrace imports or ddtrace-run to the app — SSI auto-instruments WITHOUT any code changes.
  • admission.datadoghq.com/enabled annotations — that's admission controller config injection, not SSI init container injection.

Linux APM install / instrument / onboard — trigger when the user mentions a single host, VM, EC2 instance, bare-metal, RHEL/Ubuntu/Debian, systemd, or no orchestrator.

Immediately read .claude/skills/dd-apm/linux-ssi/agent-install/SKILL.md now, then .claude/skills/dd-apm/linux-ssi/enable-ssi/SKILL.md, then .claude/skills/dd-apm/linux-ssi/verify-ssi/SKILL.md — do not proceed from memory.

Do NOT install the agent via plain apt-get install datadog-agent (or yum equivalent) and assume SSI follows — host auto-instrumentation requires the install script with the SSI flags, which the sub-skill walks through.


Service rename / service remapping — trigger when the user mentions renaming a service, collapsing multiple service names, stripping suffixes/prefixes, or cleaning up inferred services.

Immediately read .claude/skills/dd-apm/service-remapping/SKILL.md now — do not proceed from memory.

Do NOT change tags.datadoghq.com/service labels or DD_SERVICE env vars to rename a service in Datadog. That requires a rollout and only affects new data. Use a service remapping rule — it rewrites the name at ingestion time with no deployment change.


Overlap disambiguation

When a request could plausibly fit more than one entry above, use these tiebreakers:

HintRoute to
Cluster orchestrator mentioned (EKS/GKE/AKS/kind/K3s/minikube) — even if "just one node"k8s-ssi
Single host, VM, or EC2 with no orchestratorlinux-ssi
"Several services that should be one"service-remapping — the sub-skill picks the rule type based on whether the duplicates are real instrumented services or inferred entities (DBs, queues, external APIs)
"My service shows under the wrong name"First check DD_SERVICE on the deploy. If correct and the name is still wrong → service-remapping.
"Reduce APM volume / cost / noise"No sub-skill yet. Ask whether the user means sampling (fewer ingested traces) or retention filters (less indexed data) before suggesting commands.

None of the above

If the request doesn't match any entry above, continue reading the trace-search, service analysis, and metrics content below. If even that doesn't fit, ask the user to clarify — do not invent a workflow.


Requirements

Datadog Labs Pup should be installed. See Setup Pup if not.

Command Execution Order (Token-Efficient)

For scoped commands, use this order:

  1. Check context first (prior outputs, conversation, saved values).
  2. If a required value is missing, run a discovery command first.
  3. If still ambiguous, ask the user to confirm.
  4. Then run the target command.
  5. Avoid speculative commands likely to fail.

Quick Start

bash
pup auth login
# Confirm env tag with the user first (do not assume production/prod/prd).
pup apm services list --env <env> --from 1h --to now
pup traces search --query "service:api-gateway" --from 1h

Services

List Services

bash
pup apm services list --env <env> --from 1h --to now
pup apm services stats --env <env> --from 1h --to now

Service Stats

bash
pup apm services stats --env <env> --from 1h --to now

Service Map

bash
# View dependencies
pup apm flow-map --query "service:api-gateway&from=$(($(date +%s)-3600))000&to=$(date +%s)000" --env <env> --limit 10

Traces

Search Traces

bash
# By service
pup traces search --query "service:api-gateway" --from 1h

# Errors only
pup traces search --query "service:api-gateway status:error" --from 1h

# Slow traces (>1s)
pup traces search --query "service:api-gateway @duration:>1000ms" --from 1h

# With specific tag
pup traces search --query "service:api-gateway @http.url:/api/users" --from 1h

Trace Detail

bash
# No direct get command for a single trace ID.
# Use traces search with a narrow query and time window.
pup traces search --query "trace_id:<trace_id>" --from 1h

Key Metrics

MetricWhat It Measures
trace.http.request.hitsRequest count
trace.http.request.durationLatency
trace.http.request.errorsError count
trace.http.request.apdexUser satisfaction

Service Level Objectives

Link APM to SLOs:

bash
pup slos create --file slo.json

Common Queries

GoalQuery
Slowest endpointsavg:trace.http.request.duration{*} by {resource_name}
Error ratesum:trace.http.request.errors{*} / sum:trace.http.request.hits{*}
Throughputsum:trace.http.request.hits{*}.as_rate()

Troubleshooting

ProblemFix
No tracesCheck ddtrace installed, DD_TRACE_ENABLED=true
Missing serviceVerify DD_SERVICE env var
Traces not linkedCheck trace headers propagated
High cardinalityDon't tag with user_id/request_id

References/Docs

Frequently asked questions

What does the Dd Apm AI skill do?

APM - install, onboard, instrument, enable, set up, configure, traces, services, dependencies, performance analysis. Use for any request involving Datadog APM setup, instrumentation (SSI, ddtrace, agent install), or analysis.

Why use Dd Apm on TypingMind?

Because you install it once and use it with any model. Dd Apm 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 Dd Apm in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/datadog-labs/agent-skills/tree/main/dd-apm. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Dd Apm?

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 Dd Apm?

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

Is the Dd Apm AI skill free?

Yes. It is published on GitHub by datadog-labs under the MIT 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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