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datadog-labs/agent-skills4 files

Dd Browser SDK

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Specification
Skill ID
datadog-labs/agent-skills/dd-browser-sdk
Publisher
datadog-labs
Repository
agent-skills
Installs
0
Files
4
Synced
Sep 23, 2026
How to use it

Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.

datadog-labs/agent-skills/dd-browser-sdkInstalls these files
  • SKILL.md
  • upgrade-v5/SKILL.md
  • upgrade-v6/SKILL.md
  • upgrade-v7/SKILL.md

What this skill tells the agent

Datadog Browser SDK

RUM, Logs, and Session Replay instrumentation for browser applications.

Skills

TaskSkill
Upgrade from v4 to v5dd-browser-sdk/upgrade-v5
Upgrade from v5 to v6dd-browser-sdk/upgrade-v6
Upgrade from v6 to v7dd-browser-sdk/upgrade-v7

Routing

Upgrading from v4 to v5 (removed options like proxyUrl, sampleRate, replaySampleRate, premiumSampleRate, allowedTracingOrigins, deprecated APIs like addRumGlobalContext, removeUser, or /v4/ CDN paths):

Immediately read .claude/skills/dd-browser-sdk/upgrade-v5/SKILL.md — do not proceed from memory.

Upgrading from v5 to v6 (removed options like useCrossSiteSessionCookie, sendLogsAfterSessionExpiration, dropping IE11 support, or /v5/ CDN paths):

Immediately read .claude/skills/dd-browser-sdk/upgrade-v6/SKILL.md — do not proceed from memory.

Upgrading from v6 to v7 (removed options like betaEncodeCookieOptions, allowFallbackToLocalStorage, trackBfcacheViews, usePciIntake, or /v6/ CDN paths):

Immediately read .claude/skills/dd-browser-sdk/upgrade-v7/SKILL.md — do not proceed from memory.

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Install the Datadog Agent on Kubernetes using the Datadog Operator — required before enabling Single Step Instrumentation (SSI), which automatically instruments applications for APM without code changes. Only use if no Datadog Agent is deployed on the cluster yet.

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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 suite", "publish evaluators", or wants to generate BaseEvaluator/LLMJudge code or online judge configs from production LLM trace data. Works with ml_app and optional RCA report or failure hypothesis.

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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-observability-session-classify`, `agent-observability-trace-rca`, `agent-observability-eval-bootstrap`, `agent-observability-experiment-bootstrap`, `agent-observability-experiment-analyzer`). Use when user says "run the eval pipeline", "go from traces to evals", "bootstrap evals end to end", "classify then RCA then bootstrap", "build an eval set from scratch", "onboard me to datasets and experiments", "walk me through experiments", "I have an ml_app, now what", "Agent Observability onboarding", "guided experiment setup", "from traces to experiments", or wants a deterministic, narrated tour from production data through evaluators, datasets, and experiments. Stop early with `--stop-after <phase>` to short-circuit at evaluators or dataset, or resume mid-flow with `--start-at <phase>`.

Use this skill in a project

Open any RiverX project, search the Skills panel for datadog-labs/agent-skills/dd-browser-sdk, and install it in one click.

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