agent-skills

In the author's own words, from each skill's SKILL.md — showing the first 30 of 49 files.

• agent-skills

  Datadog skills for AI agents. Essential monitoring, logging, tracing and observability.

  SKILL.md on GitHub (opens in a new tab)

• dd-account-setup

  Ensure the user has an authenticated Datadog account with a valid DD_API_KEY on the right region before any Datadog setup or instrumentation. Detects existing DD_API_KEY / DD_APP_KEY / DD_SITE, validates them against the Datadog API, and fixes the common wrong-region 403. If no usable key exists, signs the user in (OAuth) or creates a new account, then obtains and validates a key. Use this whenev…

  dd-account-setup/SKILL.md on GitHub (opens in a new tab)

• 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.

  dd-apm/SKILL.md on GitHub (opens in a new tab)

• dd-audit

  Audit Trail investigations - who changed what, key compromise, cost spike root cause, compliance evidence (SOC 2/PCI), and AI activity auditing.

  dd-audit/SKILL.md on GitHub (opens in a new tab)

• dd-aws-integration

  Set up the Datadog AWS integration with Terraform - creates the cross-account IAM role Datadog assumes (external ID, no stored credentials), attaches the permission policies Datadog publishes, and registers the account through datadog_integration_aws_account so AWS metrics, the resource catalog, and CSPM findings start flowing. Use when the user has AWS resources they want to monitor, wants to co…

  dd-aws-integration/SKILL.md on GitHub (opens in a new tab)

• dd-azure-integration

  Set up the Datadog Azure integration with Terraform - creates an Entra ID app registration and service principal, assigns Monitoring Reader across the chosen subscriptions and management groups, grants the Microsoft Graph permissions Datadog needs for resource discovery, and registers the tenant so Azure metrics and resource collection start flowing. Use when the user wants to monitor Azure VMs,…

  dd-azure-integration/SKILL.md on GitHub (opens in a new tab)

• dd-browser-sdk

  Datadog Browser SDK — RUM, Logs, Session Replay, profiling, product analytics, and error tracking setup, configuration, and migration. Use when upgrading Browser SDK versions, setting up RUM or Logs, or troubleshooting browser-side Datadog instrumentation.

  dd-browser-sdk/SKILL.md on GitHub (opens in a new tab)

• dd-docs

  Datadog docs lookup using docs.datadoghq.com/llms.txt and linked Markdown pages.

  dd-docs/SKILL.md on GitHub (opens in a new tab)

• dd-gcp-integration

  Set up the Datadog Google Cloud integration with Terraform - creates a service account in the host project, lets Datadog's delegate principal impersonate it via roles/iam.serviceAccountTokenCreator (no service-account keys), enables the required APIs, grants the monitoring roles across the chosen projects and folders, and registers the account through datadog_integration_gcp_sts. Use when the use…

  dd-gcp-integration/SKILL.md on GitHub (opens in a new tab)

• dd-instrument-rum

  Instrument browser-based web applications with Datadog Browser RUM. Detect the application framework, router, package manager, bundler, entrypoint, credentials, and existing RUM setup; add or safely complete classic Browser RUM instrumentation for React, Next.js App or Pages Router, Angular, Vue, Nuxt, Svelte, vanilla JavaScript, SPAs, and iframe-hosted apps; avoid duplicate initialization; and v…

  dd-instrument-rum/SKILL.md on GitHub (opens in a new tab)

• dd-logs

  Log management - search, archives, metrics, and cost control.

  dd-logs/SKILL.md on GitHub (opens in a new tab)

• dd-monitors

  Monitor management - list, search, file-based create, and alerting best practices.

  dd-monitors/SKILL.md on GitHub (opens in a new tab)

• dd-oci-integration

  Set up the Datadog Oracle Cloud Infrastructure (OCI) integration with Terraform - verifies ~/.oci/config, then applies Datadog's official oracle-cloud-integration module to create the Datadog service user, group, IAM policies, and API key in the tenancy and register it with Datadog, optionally including log collection. Use when the user has Oracle Cloud resources, wants to monitor an OCI tenancy,…

  dd-oci-integration/SKILL.md on GitHub (opens in a new tab)

• dd-orchestrator

  Entry point for Datadog onboarding. Takes a developer's plain-language goal, ensures a valid Datadog account with dd-account-setup, asks dd-product-recommender which products fit, detects the project's platform and cloud, then composes an ordered plan across the existing skills (agent install, product enable, verify, and optional cloud integration) and dispatches to each by source URL — honestly…

  dd-orchestrator/SKILL.md on GitHub (opens in a new tab)

• dd-product-recommender

  Recommends the right Datadog products for a codebase and/or a stated goal — grounded in a tech-stack→product map and a use-case→product map built from Datadog product capabilities and common technology patterns. Recommendation only; no setup instructions. Use when a user asks which Datadog products fit their app, what to monitor, or which products serve a goal like security, cost, or LLM observab…

  dd-product-recommender/SKILL.md on GitHub (opens in a new tab)

• dd-pup

  Datadog CLI (Rust). OAuth2 auth with token refresh.

  dd-pup/SKILL.md on GitHub (opens in a new tab)

• agent-observability-auto-experiment

  Run an iterative code-improvement hill-climb against real Datadog LLM-Obs data, locally, with Claude Code as the agent. Establishes a baseline eval, makes one focused change, re-scores with the same harness, keeps the change if it improves the score in the goal's direction (labeling within-noise gains tentative), and repeats. Use when the user says "run an auto experiment", "hill-climb this code"…

  agent-observability/agent-observability-auto-experiment/SKILL.md on GitHub (opens in a new tab)

• agent-observability-build-eval-from-annotations

  Fit a Datadog LLM-Obs evaluator to human labels. Takes an annotation queue, works out where in the trace the labelled property actually lives, drafts an LLM-judge that predicts the human label, scores that judge against the already-labelled rows with a metric agreed with the user, then hill-climbs it — inspect the errors, make one focused change, re-score, keep it only if it beats the best — for…

  agent-observability/agent-observability-build-eval-from-annotations/SKILL.md on GitHub (opens in a new tab)

• agent-observability-eval-bootstrap

  Bootstrap evaluators from production traces — by default propose online LLM-judge evaluators and, after you confirm, create them in Datadog as disabled drafts (never auto-enabled); on request emit Python SDK code or a framework-agnostic JSON spec instead. Use when user says "bootstrap evaluators", "generate evaluators", "create evals from traces", "eval bootstrap", "write evaluators", "build eval…

  agent-observability/agent-observability-eval-bootstrap/SKILL.md on GitHub (opens in a new tab)

• agent-observability-eval-pipeline

  End-to-end Agent Observability pipeline for an instrumented ml_app — classify production traces, root-cause failures, bootstrap evaluators, then (optionally) sample + publish a dataset, generate + run an experiment, and analyze results. Six narrated phases with a standardized banner and a "continue" checkpoint between each. Pure orchestration over the agent-observability sub-skills (`agent-observ…

  agent-observability/agent-observability-eval-pipeline/SKILL.md on GitHub (opens in a new tab)

• agent-observability-experiment-analyzer

  Analyze LLM experiment results. Handles single or comparative experiments, exploratory or Q&A modes. Use when user says "analyze experiment", "compare experiments", "analyze against baseline", or provides one or two experiment IDs for analysis.

  agent-observability/agent-observability-experiment-analyzer/SKILL.md on GitHub (opens in a new tab)

• agent-observability-experiment-bootstrap

  Bootstrap a reproducible LLM Observability experiment through the Python ddtrace SDK or the Node dd-trace SDK. Use for experiment, dataset, evaluator, benchmark, regression, or LLM-as-a-judge scaffolding. The legacy Python invocation remains supported.

  agent-observability/agent-observability-experiment-bootstrap/SKILL.md on GitHub (opens in a new tab)

• agent-observability-replay-trace

  Use when a developer wants to iterate on ONE specific Agent Observability / LLM Obs trace whose output they didn't like — re-running that trace against their LOCAL code, seeing a concise diff of the old vs new output, and looping (change code → replay → diff) until satisfied. Invoked as /agent-observability-replay-trace <trace-id> [changes to test]. Signals: "replay this trace"; "iterate on a tra…

  agent-observability/agent-observability-replay-trace/SKILL.md on GitHub (opens in a new tab)

• agent-observability-session-classify

  Classify whether user intent was satisfied in a Datadog Agent Observability trace or session. Three modes: (1) session_id — classify a single CMD+I assistant session with RUM; (2) trace_id — classify a single Agent Observability trace without RUM; (3) ml_app — sample and classify multiple sessions or traces from a given LLM app. Output is compact by default (verdict + one-sentence reason). Use wh…

  agent-observability/agent-observability-session-classify/SKILL.md on GitHub (opens in a new tab)

• agent-observability-trace-rca

  Root cause analysis on production LLM traces. Diagnoses why an LLM application is failing — works from eval judge verdicts, runtime errors, or structural anomalies depending on what signals are present. Walks the span tree from symptom to root cause. Use when user says "what's wrong with my app", "why is my eval failing", "analyze errors", "root cause analysis", "diagnose failures", or wants to u…

  agent-observability/agent-observability-trace-rca/SKILL.md on GitHub (opens in a new tab)

• service-remapping

  Create and manage APM service remapping rules — rewrite service names at ingestion time to collapse noisy inferred entities, clean up auto-generated names, handle org renames, or normalize naming conventions. Use for any request involving service renaming, service mapping, inferred service cleanup, peer.service normalization, or collapsing fragmented service names.

  dd-apm/service-remapping/SKILL.md on GitHub (opens in a new tab)

• datadog-app

  Guides developers building Datadog Apps with TypeScript, React, the @datadog/apps scaffolder, and @datadog/vite-plugin. Use when a user wants to scaffold, run, debug, upgrade, build, upload, publish, upload without publishing (draft upload), add an upload-no-publish script, set up CI/CD, use OAuth or API/application key auth, trigger/poll Workflow Automation, choose DDSQL or Action Catalog for ba…

  dd-apps/datadog-app/SKILL.md on GitHub (opens in a new tab)

• dd-audit-ai-activity

  Audit what the Bits AI assistant (MCP server) has done in your Datadog org — tool calls by user, resources accessed, and anomaly flags for AI governance.

  dd-audit/ai-activity-audit/SKILL.md on GitHub (opens in a new tab)

• dd-audit-compliance-report

  Generate auditor-ready compliance evidence from Datadog Audit Trail for SOC 2 and PCI DSS. Maps framework controls to specific query patterns and produces formatted output.

  dd-audit/compliance-report/SKILL.md on GitHub (opens in a new tab)

• dd-audit-cost-spike-investigation

  Investigate a Datadog product usage or cost spike by correlating Usage Metering data (when/what spiked) with Audit Trail config changes (who changed what in the preceding window).

  dd-audit/cost-spike-investigation/SKILL.md on GitHub (opens in a new tab)

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