agent-skills

Name: agent-skills
Author: datadog-labs

github.com/datadog-labsCloud & DevOps1802.6k installsUpdated 6d ago

About agent-skills

A collection of Datadog skills for AI agents, covering account setup, monitoring, logs, observability, and cloud integrations. It also guides use of the `pup` CLI and sets an execution policy that checks context and discovers missing inputs before running commands.

Key features

01Authenticate Datadog accounts and check regions
02Search logs, traces, and metrics
03Create and manage monitors and alerts
04Configure cloud integrations and SDKs
05Manage tasks with the `pup` CLI

Use cases

01Investigate application errors and slow traces
02Create alerts or schedule monitor downtime
03Connect cloud accounts to Datadog
04Instrument AI backends for LLM observability

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/datadog-labs/agent-skills --skill agent-skills

After installing, type/agent-skillsin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

Cargo.toml

.gitignore

LICENSE

README.md

agent-observability/agent-observability-auto-experiment/references/

eval_harness_template.py

eval_harness_template.mjs

rubrics.md

agent-observability/agent-observability-build-eval-from-annotations/references/

judge_runner.py

rubrics.md

scoring.py

agent-observability/agent-observability-eval-pipeline/scripts/

.gitignore

publish_dataset.py

load_env.py

agent-observability/agent-observability-experiment-analyzer/evals/

__init__.py

example_config.json

evaluator.py

executor.py

agent-observability/agent-observability-experiment-analyzer/evals/data/

experiment_analyzer_v0.json

experiment_analyzer_v1.json

agent-observability/agent-observability-experiment-analyzer/evals/prompts/

judge_rubric.txt

agent-observability/agent-observability-experiment-bootstrap/references/node/

nodejs.md

agent-observability/agent-observability-experiment-bootstrap/references/python/

env_setup_template.py

agent-observability/agent-observability-experiment-bootstrap/references/python/evaluator-styles/

function.md

class.md

remote.md

agent-observability/agent-observability-experiment-bootstrap/references/python/providers/

anthropic.md

gemini.md

langchain.md

llamaindex.md

bedrock.md

Details

From the project README

Datadog Skills

Essential Datadog skills for AI agents.

Core Skills

Skill	Description
dd-account-setup	Ensure an authenticated Datadog account with a valid API key on the right region; validates keys, fixes wrong-region 403s, signs in or creates an account
dd-android-sdk	Route Datadog Android SDK upgrades to the migration instructions for the project's current and target major versions.
dd-apm	Traces, services, performance analysis
dd-apps	Build Datadog Apps — scaffold, run, upload, publish, CI/CD
dd-aws-integration	Connect an AWS account to Datadog with Terraform - cross-account IAM role, metrics and resource collection
dd-azure-integration	Connect Azure subscriptions or management groups to Datadog with Terraform - Entra app registration, Monitoring Reader
dd-browser-sdk	Browser SDK setup, RUM, Logs, Session Replay, version migration
dd-docs	Search Datadog documentation
dd-gcp-integration	Connect GCP projects or folders to Datadog with Terraform - keyless service-account impersonation
dd-instrument-llmo	Instrument Python & Node.js/Next.js AI backends with Datadog LLM Observability — SDK init, agent/workflow spans, RUM↔LLMO session linking
dd-instrument-rum	Instrument browser apps with Datadog Browser RUM — React, Next.js, Angular, Vue, Nuxt, Svelte, vanilla
dd-llmo	LLM Observability traces, experiments, evals
dd-logs	Search logs, pipelines, archives
dd-monitors	Create, manage, mute monitors and alerts
dd-oci-integration	Connect an Oracle Cloud tenancy to Datadog with Terraform - Datadog's official OCI module
dd-product-recommender	Recommend the right Datadog products for a codebase and/or goal (recommendation only)
dd-pup	Primary CLI - all pup commands, auth, PATH setup
dd-software-delivery	CI/CD workflow skills — unblock PR, triage flaky tests

Install

# Install core skills
npx skills add datadog-labs/agent-skills \
  --skill dd-pup \
  --skill dd-monitors \
  --skill dd-logs \
  --skill dd-apm \
  --skill dd-docs \
  --full-depth -y

# Install CI/CD workflow skills
npx skills add datadog-labs/agent-skills \
  --skill dd-software-delivery/unblock-pr \
  --skill dd-software-delivery/triage-flaky-test \
  --full-depth -y

Prerequisites

See Setup Pup for installation and authentication.

Command Execution Policy

Use this order for scoped commands:

Check context first (conversation, prior outputs, known values).
Run discovery commands when required values are missing.
Ask the user only when values remain ambiguous.
Run the target command after required inputs are known.
Avoid speculative commands likely to fail.

Quick Reference

Task	Command
Search error logs	`pup logs search --query "status:error" --from 1h`
List monitors	`pup monitors list`
Schedule monitor downtime	`pup downtime create --file downtime.json`
Find slow traces	`pup traces search --query "service:api @duration:>500ms" --from 1h`
Query metrics	`pup metrics query --query "avg:system.cpu.user{*}"`
Check auth	`pup auth status`
Refresh token	`pup auth refresh`

Auth

pup auth login          # OAuth2 (recommended)
pup auth status         # Check token
pup auth refresh        # Refresh expired token

Token Expiry: OAuth tokens expire (~1 hour). Run pup auth refresh if commands fail with 401/403.

More Skills

Additional skills available shortly.

npx skills add datadog-labs/agent-skills --list --full-depth

Comments

Markdown supported

Details

Author: datadog-labs
Repository: datadog-labs/agent-skills
Category: Cloud & DevOps
Installs: 2,647
GitHub stars: 180

Report

More skills

All skills

lark-apps

open.feishu.cn

732.0k

Develop and host Miaoda (Spark/Miaoda) apps: app creation, local full-stack development, cloud generation and iteration, creative design (UI mockups / interactive prototypes / wireframes / landing pages / dashboards / slide decks / visual exploration), integration of AI-related capabilities, Feishu platform capabilities, or other external capabilities; log/Trace/monitoring metric/PV/UV queries; environment variable management; app collaborators and collaboration permissions; app roles and members; and automation triggers (scheduled / record changes / Webhook / Feishu approvals). Use when users want to develop or create a system, tool, platform, or app; develop locally or in the cloud, modify, deploy, publish, launch, or get a shareable link; create a page or website with HTML and deploy it to Miaoda; design, create a mockup, prototype, wireframe, PPT, deck, or visual exploration; or mention Miaoda/Spark/Miaoda apps (links like `/app/app_xxx` or `/page/<token>`, runtime domains like *.aiforce.cloud), app databases, app file storage, open API Keys, visibility, app collaborators/developer permissions, app roles/role members, production logs, API request volume, error volume, latency, traffic, environment variables, or setting up automation tasks, scheduled triggers, or approval-triggered automation for Miaoda apps. Not for regular cloud drive file uploads (lark-drive), Feishu document editing (lark-doc), or native slide creation (lark-slides).

azure-prepare

github.com/microsoft

571.7k

Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure, modernize app for Azure with azd, deploy with azd, function app, timer trigger, service bus trigger, event-driven function, managed identity, generate Bicep, generate Terraform, create and deploy to Azure.

wizard

github.com/mattpocock

571.5k

Generate an interactive bash wizard that walks a human through steps only they can perform. Use when provisioning infrastructure, setting up credentials or CI secrets, walking an unfamiliar third-party dashboard, or running a one-off migration or cutover. Don't invoke this for steps the agent can perform itself.

azure-ai

github.com/microsoft

571.2k

Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.