Official agent skill

Llmobs Integration

A skill your agent uses when adding, debugging, or modifying LLMObs plugins for an LLM library in dd-trace-js.

OfficialCustom licenceAuto-check passedAI & LLM Engineering

Install Llmobs Integration

skills CLI

$ npx skills add DataDog/dd-trace-js --skill llmobs-integration -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install DataDog/dd-trace-js llmobs-integration --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/DataDog/dd-trace-js.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/llmobs-integration .claude/skills/llmobs-integration && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "llmobs-integration" agent skill from https://github.com/DataDog/dd-trace-js/tree/master/.agents/skills/llmobs-integration into .claude/skills/llmobs-integration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llmobs-integration", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/DataDog/dd-trace-js/tree/master/.agents/skills/llmobs-integration

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add DataDog/dd-trace-js --skill llmobs-integration -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install DataDog/dd-trace-js llmobs-integration --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/DataDog/dd-trace-js.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/llmobs-integration .agents/skills/llmobs-integration && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "llmobs-integration" agent skill from https://github.com/DataDog/dd-trace-js/tree/master/.agents/skills/llmobs-integration into .agents/skills/llmobs-integration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llmobs-integration", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add DataDog/dd-trace-js --skill llmobs-integration -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install DataDog/dd-trace-js llmobs-integration --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/DataDog/dd-trace-js.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/llmobs-integration .cursor/skills/llmobs-integration && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "llmobs-integration" agent skill from https://github.com/DataDog/dd-trace-js/tree/master/.agents/skills/llmobs-integration into .cursor/skills/llmobs-integration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llmobs-integration", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/DataDog/dd-trace-js.git --path .agents/skills/llmobs-integration

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add DataDog/dd-trace-js --skill llmobs-integration -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install DataDog/dd-trace-js llmobs-integration --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/DataDog/dd-trace-js.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/llmobs-integration .gemini/skills/llmobs-integration && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "llmobs-integration" agent skill from https://github.com/DataDog/dd-trace-js/tree/master/.agents/skills/llmobs-integration into .gemini/skills/llmobs-integration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llmobs-integration", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install DataDog/dd-trace-js llmobs-integration

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add DataDog/dd-trace-js --skill llmobs-integration -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/DataDog/dd-trace-js.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/llmobs-integration .github/skills/llmobs-integration && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "llmobs-integration" agent skill from https://github.com/DataDog/dd-trace-js/tree/master/.agents/skills/llmobs-integration into .github/skills/llmobs-integration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llmobs-integration", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add DataDog/dd-trace-js --skill llmobs-integration -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install DataDog/dd-trace-js llmobs-integration --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/DataDog/dd-trace-js.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/llmobs-integration .opencode/skills/llmobs-integration && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "llmobs-integration" agent skill from https://github.com/DataDog/dd-trace-js/tree/master/.agents/skills/llmobs-integration into .opencode/skills/llmobs-integration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llmobs-integration", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: llmobs-integration
GitHub stars: 836
Token cost: ~1.4k tokens
SKILL.md length: 628 words
Files: 5 (incl. references)
Skills in repo: 7
Repo updated: Oct 7, 2026
First seen: Oct 7, 2026
Licence: Custom licence

At a glance

A skill your agent uses when adding, debugging, or modifying LLMObs plugins for an LLM library in dd-trace-js.

Works in 4 steps: LLMObsPlugin Base Class → Package Shape → LLM Span Kinds → …
Modifying LLMObs plugins for an LLM library in dd-trace-js
SKILL.md covers Read Upstream Source First, Core Concepts and Implementation Steps
Calls npm

What it does

Llmobs Integration is an agent skill from DataDog/dd-trace-js, published by the product's own GitHub organization. Use when adding, debugging, or modifying LLMObs plugins for an LLM library in dd-trace-js. Triggers: "add LLMObs support", "instrument chat completions / streaming / embeddings / agent runs / orchestration / tool calls / retrieval", "LLMObsPlugin", "getLLMObsSpanRegisterOptions", "setLLMObsTags", "SPANKINDS", "span kind", any provider tag ("openai" / "anthropic" / "genai" / "google" / "langchain" / "langgraph" / "ai" llmobs), "VCR cassettes".

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `references/category-detection.md`, `references/message-extraction.md` and `references/plugin-architecture.md`).

It sits in AI & LLM Engineering, covering Building AI agents, LLM API integration and Embeddings. It works with OpenAI, Datadog, LangChain and LangGraph. The repository describes itself as: Datadog APM client for Node.js.

When your agent uses it

Modifying LLMObs plugins for an LLM library in dd-trace-js
Tasks that involve Building AI agents
Tasks that involve LLM API integration

Example prompts

“add LLMObs support”
“LLMObsPlugin”
“getLLMObsSpanRegisterOptions”
“/llmobs-integration”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

LLMObsPlugin Base Class
Package Shape
LLM Span Kinds
Message Extraction

What it can do on your machine

Read from SKILL.md and the folder at commit 8002f70. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- npm
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Llmobs Integration loads about 1.4k tokens when it runs, and up to ~5.8k if it reads all its reference files. Until then it costs about 117 tokens; SKILL.md has 628 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~117
When it runs · the whole SKILL.md, loaded when a task matches: ~1.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~5.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 628 words (~1,445 tokens).

“This skill covers creating LLMObs plugins that instrument LLM library operations and emit span events. Supported operations: chat completions (streaming and non-streaming), embeddings, agent runs, orchestration (workflows / graphs), tool calls, retrieval (RAG / vector DB).”

— opening of SKILL.md by DataDog, Custom licence

name: llmobs-integration

Read the full SKILL.md on GitHub

Files

SKILL.md and 4 other files (references) in .agents/skills/llmobs-integration of DataDog/dd-trace-js.

SKILL.md
references/category-detection.md
references/message-extraction.md
references/plugin-architecture.md
references/reference-implementations.md

Open the folder on GitHubat commit 8002f70

Compare with similar skills

Llmobs Integration next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Llmobs Integration compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Llmobs Integration this skillDataDog/dd-trace-js	836	—	~1.4k	Automated safety check: Pass	Custom licence	today
Sap Cloud SDK AIsecondsky/sap-skills	460	—	~3.2k	Automated safety check: Pass	GPL-3.0	2 days ago
Sap Cloud SDK AI Pythonsecondsky/sap-skills	460	—	~3.8k	Automated safety check: Pass	GPL-3.0	2 days ago
Add Example AgentGetBindu/Bindu	10k	—	~1.1k	Automated safety check: Notes	Custom licence	1 mo ago
Agent Prompt Engineeringagentailor/fullstack-langgraph-nextjs-agent	132	—	~3.6k	Automated safety check: Pass	MIT	1 mo ago
Agent Inspectrajudandigam/agent-inspect	165	—	~424	Automated safety check: Pass	MIT	today

Similar skills

Sap Cloud SDK AI
secondsky/sap-skills
Integrates SAP Cloud SDK for AI into JavaScript/TypeScript and Java applications.
460 GitHub stars~3.2k tokensUpdated 2 days ago
AI & LLM EngineeringAuto-check passed
Sap Cloud SDK AI Python
secondsky/sap-skills
Integrates the SAP Cloud SDK for AI for Python (sap-ai-sdk-gen, formerly generative-ai-hub-sdk) into Python applications.
460 GitHub stars~3.8k tokensUpdated 2 days ago
AI & LLM EngineeringAuto-check passed
Add Example Agent
GetBindu/Bindu
Add a new self-contained example agent under examples/. An agent skill from GetBindu/Bindu.
10k GitHub stars~1.1k tokensUpdated 1 mo ago
AI & LLM EngineeringAuto-check: notes
Agent Prompt Engineering
agentailor/fullstack-langgraph-nextjs-agent
Comprehensive guide for designing, refining, and auditing system prompts for autonomous AI agents based on Anthropic's production practices.
132 GitHub stars~3.6k tokensUpdated 1 mo ago
AI & LLM EngineeringAuto-check passed
Agent Inspect
rajudandigam/agent-inspect
Local evidence debugger and trajectory-test toolkit for TypeScript AI agents.
165 GitHub stars~424 tokensUpdated today
AI & LLM EngineeringAuto-check passed
Tool Design
agentailor/fullstack-langgraph-nextjs-agent
Design and verify tools that AI agents can actually use — for any framework or language (MCP servers, LangChain/LangGraph, function-calling, raw JSON schema; TypeScript, Python, or otherwise).
132 GitHub stars~3.2k tokensUpdated 1 mo ago
AI & LLM EngineeringAuto-check passed

More from DataDog/dd-trace-js

Apm Integrations
DataDog/dd-trace-js
Official
A skill your agent uses when adding, debugging, fixing, or modifying instrumentation and plugins for third-party libraries in dd-trace-js.
836 GitHub stars~3k tokensUpdated today
Auto-check passed
Llmobs Testing
DataDog/dd-trace-js
Official
A skill your agent uses when writing, modifying, or debugging tests for an LLMObs plugin in dd-trace-js.
836 GitHub stars~2k tokensUpdated today
Auto-check passed
Serverless Integrations
DataDog/dd-trace-js
Official
A skill your agent uses when adding, modifying, debugging, or reviewing dd-trace-js serverless platform integrations that create root invocation spans for AWS Lambda, Azure Functions, Google Cloud…
836 GitHub stars~1.1k tokensUpdated today
Auto-check passed
Architecture Review
DataDog/dd-trace-js
Official
A skill your agent uses when a dd-trace-js change introduces or substantially changes a class hierarchy, module boundary, shared helper layer, public API, or duplicated behavior across multiple types.
836 GitHub stars~1.1k tokensUpdated today
Auto-check passed
Flaky Test Fixer
DataDog/dd-trace-js
Official
A skill your agent uses when classifying, investigating, or fixing a suspected flaky test, intermittent test result, nondeterministic CI test failure, timing race, hang, or test-order dependency in…
836 GitHub stars~1.6k tokensUpdated today
Auto-check passed
Test Optimization Testing
DataDog/dd-trace-js
Official
Validate v5 compatibility when adding or modifying Test Optimization or test framework integration tests in dd-trace-js.
836 GitHub stars~492 tokensUpdated today
Auto-check passed

Works with

Questions about Llmobs Integration

What does Llmobs Integration do?

A skill your agent uses when adding, debugging, or modifying LLMObs plugins for an LLM library in dd-trace-js. Llmobs Integration is an agent skill from DataDog/dd-trace-js, published by the product's own GitHub organization. Use when adding, debugging, or modifying LLMObs plugins for an LLM library in dd-trace-js.

When should I use Llmobs Integration?

Llmobs Integration fits situations like: modifying LLMObs plugins for an LLM library in dd-trace-js; tasks that involve Building AI agents; tasks that involve LLM API integration.

How do I install Llmobs Integration in Claude Code?

Run `npx skills add DataDog/dd-trace-js --skill llmobs-integration -a claude-code`. Or copy the skill folder (.agents/skills/llmobs-integration in DataDog/dd-trace-js) into .claude/skills/llmobs-integration in your project. Claude Code loads it when a task matches its description.

How do I install Llmobs Integration in Codex?

Run `npx skills add DataDog/dd-trace-js --skill llmobs-integration -a codex`. Or copy the skill folder (.agents/skills/llmobs-integration in DataDog/dd-trace-js) into .agents/skills/llmobs-integration in your project. Codex loads it when a task matches its description.

Can I use Llmobs Integration in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add DataDog/dd-trace-js --skill llmobs-integration -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/llmobs-integration, .gemini/skills/llmobs-integration, .github/skills/llmobs-integration and .opencode/skills/llmobs-integration in your project.

What does Llmobs Integration need to run?

Going by SKILL.md and its folder, Llmobs Integration needs the command-line tools its instructions call (npm).

Does Llmobs Integration access the network?

SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Llmobs Integration safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Llmobs Integration use?

Llmobs Integration has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Llmobs Integration use?

About 1.4k tokens (SKILL.md is roughly 5.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.3k tokens, read only when the agent opens those files.

What are the alternatives to Llmobs Integration?

Skills that share tags, products or a category with Llmobs Integration: Sap Cloud SDK AI (secondsky/sap-skills, 460 stars), Sap Cloud SDK AI Python (secondsky/sap-skills, 460 stars), Add Example Agent (GetBindu/Bindu, 10k stars) and Agent Prompt Engineering (agentailor/fullstack-langgraph-nextjs-agent, 132 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Llmobs Integration?

DataDog (a GitHub organization, an official publisher) maintains it in DataDog/dd-trace-js, which has 836 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on October 7, 2026.

Source: DataDog/dd-trace-js on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Llmobs Integration

Facts

At a glance

What it does

When your agent uses it

Example prompts

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Files

Compare with similar skills

Similar skills

More from DataDog/dd-trace-js

Related

Questions about Llmobs Integration