Datadog logo

Datadog

OrganizationPopular
nexu-io
datadog

Use when the user says "check Datadog", "查 Datadog", "查日志", "check logs", "crash logs", "查 crash", "gateway crash", "查告警", "check alerts", "check metrics", or needs to investigate production issues via Datadog Logs API.

Overview

Publishernexu-io
Repositorynexu
Skill namedatadog
Stars
3.3K
Forks
263
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 nexu-io on GitHub. Read the source before you install it.

Installation

Install the Datadog 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/nexu-io/nexu.git /tmp/nexu
mkdir -p .claude/skills
cp -r /tmp/nexu/skills/localdev/datadog .claude/skills/datadog
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Datadog 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 Datadog 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 Datadog 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 Log Investigation

Query Datadog Logs API to investigate production issues for the Nexu platform.

Authentication

Before making any Datadog API call, you MUST ask the user for these two keys:

  • DD_API_KEY — Datadog API Key (Organization Settings → API Keys)
  • DD_APP_KEY — Datadog Application Key (Organization Settings → Application Keys, requires logs_read_data scope)

Store them in shell variables for the session. Never hardcode or commit them.

Site: datadoghq.com (US)

API Base

All requests go to https://api.datadoghq.com/api/v2/logs/events/search.

Headers:

DD-API-KEY: <api_key>
DD-APPLICATION-KEY: <app_key>
Content-Type: application/json

Common Queries

OpenClaw Crash Events

bash
curl -s "https://api.datadoghq.com/api/v2/logs/events/search" \
  -H "DD-API-KEY: $DD_API_KEY" \
  -H "DD-APPLICATION-KEY: $DD_APP_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "filter": {
      "query": "service:nexu-gateway @event:openclaw_crash",
      "from": "now-1h",
      "to": "now"
    },
    "sort": "-timestamp",
    "page": {"limit": 20}
  }'

Key fields in results:

  • attributes.attributes.exitCode — process exit code (1 = fatal error, null = signal)
  • attributes.attributes.signal — kill signal (SIGKILL, SIGTERM, etc.)
  • attributes.tagspod_name, image_tag — which pod and which version

OpenClaw stderr Output (Crash Details)

bash
curl -s "https://api.datadoghq.com/api/v2/logs/events/search" \
  -H "DD-API-KEY: $DD_API_KEY" \
  -H "DD-APPLICATION-KEY: $DD_APP_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "filter": {
      "query": "service:nexu-gateway @stream:stderr",
      "from": "now-1h",
      "to": "now"
    },
    "sort": "-timestamp",
    "page": {"limit": 50}
  }'

This shows the actual error output from the OpenClaw process (e.g., invalid_auth, EADDRINUSE, config validation failures).

Gateway Startup / Recovery Events

bash
curl -s "https://api.datadoghq.com/api/v2/logs/events/search" \
  -H "DD-API-KEY: $DD_API_KEY" \
  -H "DD-APPLICATION-KEY: $DD_APP_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "filter": {
      "query": "service:nexu-gateway (\"starting gateway\" OR \"gateway is ready\" OR \"spawned openclaw\")",
      "from": "now-1h",
      "to": "now"
    },
    "sort": "timestamp",
    "page": {"limit": 30}
  }'

Slack Token Health Check

bash
curl -s "https://api.datadoghq.com/api/v2/logs/events/search" \
  -H "DD-API-KEY: $DD_API_KEY" \
  -H "DD-APPLICATION-KEY: $DD_APP_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "filter": {
      "query": "service:nexu-api slack_token_health*",
      "from": "now-1h",
      "to": "now"
    },
    "sort": "-timestamp",
    "page": {"limit": 20}
  }'

API HTTP Request Logs

bash
curl -s "https://api.datadoghq.com/api/v2/logs/events/search" \
  -H "DD-API-KEY: $DD_API_KEY" \
  -H "DD-APPLICATION-KEY: $DD_APP_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "filter": {
      "query": "service:nexu-api http_request @attributes.status:>=500",
      "from": "now-1h",
      "to": "now"
    },
    "sort": "-timestamp",
    "page": {"limit": 20}
  }'

Filter by Pod

Add pod_name:<name> to the query:

service:nexu-gateway pod_name:nexu-gateway-1 @event:openclaw_crash

Filter by Time Window

Use ISO 8601 timestamps:

json
{
  "from": "2026-03-10T05:00:00Z",
  "to": "2026-03-10T06:00:00Z"
}

Or relative: "now-30m", "now-1h", "now-24h".

Parsing Results

Use python3 inline to extract key fields:

bash
curl -s ... | python3 -c "
import json, sys
data = json.load(sys.stdin)
events = data.get('data', [])
print(f'Total events: {len(events)}')
for e in events:
    attrs = e['attributes']['attributes']
    tags = e['attributes']['tags']
    pod = next((t.split(':',1)[1] for t in tags if t.startswith('pod_name:')), '?')
    ts = attrs.get('time', '?')
    msg = e['attributes'].get('message', '')[:120]
    print(f'{ts} | pod={pod} | {msg}')
"

Services and Events Reference

ServiceDescription
nexu-gatewayGateway sidecar (manages OpenClaw process)
nexu-apiAPI server
EventMeaning
openclaw_crashOpenClaw process exited unexpectedly
openclaw_restart_scheduledSidecar scheduling a restart
openclaw_restart_limitMax restart attempts exceeded
openclaw_orphan_killedKilled zombie OpenClaw process
slack_token_health_check_invalidatedInvalid Slack tokens detected and marked

Tag Reference

TagExample
pod_namenexu-gateway-1, nexu-gateway-2
image_tagsha-55f13372bb72abc7db1538cca3db2bcda0d35eba
kube_stateful_setnexu-gateway

Investigation Playbook

When investigating a crash:

  1. Check crash events — get exit codes, signals, timestamps, affected pods
  2. Check stderr — get the actual error message from OpenClaw
  3. Check startup events — correlate crash with deploy times (image_tag changes)
  4. Check token health — if invalid_auth, look for slack_token_health_check_invalidated
  5. Check API logs — if API errors are contributing

Rules

  1. Never hardcode API keys in skill files or logs — always use variables
  2. Default time window — start with now-1h, expand to now-24h if needed
  3. Always parse and summarize — don't dump raw JSON to the user
  4. Correlate across services — crashes often involve both gateway and API logs
  5. Check image_tag to determine if crashes are related to a specific deployment

Frequently asked questions

What does the Datadog AI skill do?

Use when the user says "check Datadog", "查 Datadog", "查日志", "check logs", "crash logs", "查 crash", "gateway crash", "查告警", "check alerts", "check metrics", or needs to investigate production issues via Datadog Logs API.

Why use Datadog on TypingMind?

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

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

Which AI models can use Datadog?

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 Datadog?

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

Is the Datadog AI skill free?

Yes. It is published on GitHub by nexu-io 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇