Agent skill

Ag2 Telemetry

Add OpenTelemetry traces to an AG2 beta Agent via TelemetryMiddleware (autogen.beta.middleware.builtin).

Apache-2.0Auto-check passedDevOps & Cloud

Install Ag2 Telemetry

skills CLI

$ npx skills add ag2ai/build-with-ag2 --skill ag2-telemetry -a claude-code

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

GitHub CLI

$ gh skill install ag2ai/build-with-ag2 ag2-telemetry --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/ag2ai/build-with-ag2.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/ag2-telemetry .claude/skills/ag2-telemetry && 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 "ag2-telemetry" agent skill from https://github.com/ag2ai/build-with-ag2/tree/main/.agents/skills/ag2-telemetry into .claude/skills/ag2-telemetry/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ag2-telemetry", 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/ag2ai/build-with-ag2/tree/main/.agents/skills/ag2-telemetry

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 ag2ai/build-with-ag2 --skill ag2-telemetry -a codex

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

GitHub CLI

$ gh skill install ag2ai/build-with-ag2 ag2-telemetry --agent codex

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

Manual copy

$ git clone --depth 1 https://github.com/ag2ai/build-with-ag2.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/ag2-telemetry .agents/skills/ag2-telemetry && 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 "ag2-telemetry" agent skill from https://github.com/ag2ai/build-with-ag2/tree/main/.agents/skills/ag2-telemetry into .agents/skills/ag2-telemetry/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ag2-telemetry", 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 ag2ai/build-with-ag2 --skill ag2-telemetry -a cursor

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

GitHub CLI

$ gh skill install ag2ai/build-with-ag2 ag2-telemetry --agent cursor

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

Manual copy

$ git clone --depth 1 https://github.com/ag2ai/build-with-ag2.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/ag2-telemetry .cursor/skills/ag2-telemetry && 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 "ag2-telemetry" agent skill from https://github.com/ag2ai/build-with-ag2/tree/main/.agents/skills/ag2-telemetry into .cursor/skills/ag2-telemetry/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ag2-telemetry", 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/ag2ai/build-with-ag2.git --path .agents/skills/ag2-telemetry

--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 ag2ai/build-with-ag2 --skill ag2-telemetry -a gemini-cli

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

GitHub CLI

$ gh skill install ag2ai/build-with-ag2 ag2-telemetry --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/ag2ai/build-with-ag2.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/ag2-telemetry .gemini/skills/ag2-telemetry && 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 "ag2-telemetry" agent skill from https://github.com/ag2ai/build-with-ag2/tree/main/.agents/skills/ag2-telemetry into .gemini/skills/ag2-telemetry/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ag2-telemetry", 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 ag2ai/build-with-ag2 ag2-telemetry

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 ag2ai/build-with-ag2 --skill ag2-telemetry -a github-copilot

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

Manual copy

$ git clone --depth 1 https://github.com/ag2ai/build-with-ag2.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/ag2-telemetry .github/skills/ag2-telemetry && 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 "ag2-telemetry" agent skill from https://github.com/ag2ai/build-with-ag2/tree/main/.agents/skills/ag2-telemetry into .github/skills/ag2-telemetry/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ag2-telemetry", 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 ag2ai/build-with-ag2 --skill ag2-telemetry -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 ag2ai/build-with-ag2 ag2-telemetry --agent opencode

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

Manual copy

$ git clone --depth 1 https://github.com/ag2ai/build-with-ag2.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/ag2-telemetry .opencode/skills/ag2-telemetry && 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 "ag2-telemetry" agent skill from https://github.com/ag2ai/build-with-ag2/tree/main/.agents/skills/ag2-telemetry into .opencode/skills/ag2-telemetry/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ag2-telemetry", 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: ag2-telemetry
GitHub stars: 252
Token cost: ~1.9k tokens
SKILL.md length: 531 words
Files: 1
Skills in repo: 16
Repo updated: Sep 6, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Add OpenTelemetry traces to an AG2 beta Agent via TelemetryMiddleware (autogen.beta.middleware.builtin).

The user wants production-grade traces
SKILL.md covers When to use, Installation, 60-second recipe and Span hierarchy, plus 7 more sections
Calls pip
Latency analysis

What it does

Ag2 Telemetry is an agent skill from ag2ai/build-with-ag2. Add OpenTelemetry traces to an AG2 beta Agent via TelemetryMiddleware (autogen.beta.middleware.builtin). Emits spans for the full turn, each LLM call, each tool execution, and each human-input request, following the OpenTelemetry GenAI semantic conventions. Compatible with any OTLP backend — Jaeger, Grafana Tempo, Datadog, Honeycomb, Langfuse. Use when the user wants production-grade traces, latency analysis, token-usage attribution, or to ship telemetry into an existing observability stack.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in DevOps & Cloud, covering Observability, Monitoring and alerting and LLM observability. It works with OpenTelemetry, Langfuse, Datadog and Grafana. The repository describes itself as: Sample code and application showcases to get you going with AG2 (formally AutoGen). The licence is Apache-2.0.

When your agent uses it

The user wants production-grade traces
Latency analysis
Token-usage attribution
Ship telemetry into an existing observability stack

Example prompts

“/ag2-telemetry”

Requirements

Python 3
Docker

What it can do on your machine

Read from SKILL.md and the folder at commit 29eeac3. 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:
- pip
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
- opentelemetry.io
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

Ag2 Telemetry loads about 1.9k tokens when it runs. Until then it costs about 129 tokens; SKILL.md has 531 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~129
When it runs · the whole SKILL.md, loaded when a task matches: ~1.9k

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

The full file from ag2ai/build-with-ag2 at commit 29eeac3, republished under its Apache-2.0 licence (© ag2ai). 531 words, ~1,852 tokens.

Download SKILL.mdSave it as .claude/skills/ag2-telemetry/SKILL.md (or your agent's skills folder).

name: ag2-telemetry
description: Add OpenTelemetry traces to an AG2 beta `Agent` via `TelemetryMiddleware` (`autogen.beta.middleware.builtin`). Emits spans for the full turn, each LLM call, each tool execution, and each human-input request, following the OpenTelemetry GenAI semantic conventions. Compatible with any OTLP backend — Jaeger, Grafana Tempo, Datadog, Honeycomb, Langfuse. Use when the user wants production-grade traces, latency analysis, token-usage attribution, or to ship telemetry into an existing observability stack.
license: Apache-2.0

Telemetry — OpenTelemetry instrumentation

When to use

The user wants to:

See per-turn / per-call latency breakdowns
Attribute token usage across operations
Push traces to Jaeger, Grafana Tempo, Datadog, Honeycomb, Langfuse, etc.
Debug a slow agent end-to-end with structured spans rather than print statements

If they just want quick stdout debugging, point them at LoggingMiddleware instead (see ag2-middleware).

Installation

bash

pip install "ag2[openai,tracing]"

60-second recipe

python

from opentelemetry import trace
from opentelemetry.sdk.resources import Resource
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import SimpleSpanProcessor, ConsoleSpanExporter

from autogen.beta import Agent
from autogen.beta.config import OpenAIConfig
from autogen.beta.middleware.builtin import TelemetryMiddleware

# 1. Configure OpenTelemetry
resource = Resource.create({"service.name": "ag2-beta-quickstart"})
tracer_provider = TracerProvider(resource=resource)
tracer_provider.add_span_processor(SimpleSpanProcessor(ConsoleSpanExporter()))
trace.set_tracer_provider(tracer_provider)

# 2. Wire the middleware
agent = Agent(
    "assistant",
    prompt="You are a helpful assistant.",
    config=OpenAIConfig(model="gpt-4o-mini"),
    middleware=[
        TelemetryMiddleware(
            tracer_provider=tracer_provider,
            agent_name="assistant",
        ),
    ],
)

# 3. Run — spans emit automatically
import asyncio
asyncio.run(agent.ask("What is the capital of France?"))

For production, swap ConsoleSpanExporter for OTLPSpanExporter (or your backend's exporter) and SimpleSpanProcessor for BatchSpanProcessor.

Span hierarchy

Each ask() produces a root span with children:

invoke_agent assistant
  ├── chat gpt-4o-mini              # LLM API call
  ├── execute_tool get_weather      # tool execution
  ├── chat gpt-4o-mini              # LLM call after tool result
  └── await_human_input assistant   # human-in-the-loop

Span types

Every span has an ag2.span.type attribute:

`ag2.span.type`	Operation name	Hook
`agent`	`invoke_agent`	`on_turn` — full turn
`llm`	`chat`	`on_llm_call` — each LLM call
`tool`	`execute_tool`	`on_tool_execution` — each tool
`human_input`	`await_human_input`	`on_human_input` — HITL

Semantic attributes (GenAI semconv)

Spans carry standard OpenTelemetry GenAI attributes:

Attribute	Spans	Description
`gen_ai.operation.name`	All	`invoke_agent` / `chat` / `execute_tool` / `await_human_input`
`gen_ai.agent.name`	agent, human_input	Agent name
`gen_ai.provider.name`	agent, llm	Auto-detected (`openai`, `anthropic`, …)
`gen_ai.request.model`	agent, llm	e.g. `gpt-4o-mini`
`gen_ai.response.model`	llm	Resolved from response
`gen_ai.response.finish_reasons`	llm	e.g. `["stop"]`, `["tool_calls"]`
`gen_ai.usage.input_tokens`	llm	Prompt tokens
`gen_ai.usage.output_tokens`	llm	Completion tokens
`gen_ai.usage.cache_creation_input_tokens`	llm	Prompt-cache writes (Anthropic)
`gen_ai.usage.cache_read_input_tokens`	llm	Prompt-cache reads (Anthropic, OpenAI, Gemini)
`gen_ai.tool.name`	tool	Tool function name
`gen_ai.tool.call.id`	tool	Tool call ID
`gen_ai.tool.type`	tool	Always `function`

Content capture (default ON)

By default, message content, tool args, and results are included on spans. Useful for debugging but can leak sensitive data:

python

TelemetryMiddleware(
    tracer_provider=tracer_provider,
    agent_name="assistant",
    capture_content=False,   # omit messages, tool args, results
)

When enabled, additional attributes appear:

Attribute	Span	Content
`gen_ai.input.messages`	llm	JSON request messages
`gen_ai.output.messages`	llm	JSON response messages
`gen_ai.tool.call.arguments`	tool	Tool args (JSON)
`gen_ai.tool.call.result`	tool	Tool result
`ag2.human_input.prompt`	human_input	Prompt shown to human
`ag2.human_input.response`	human_input	Human's response

For privacy-sensitive backends (or anywhere telemetry leaves your infra), set capture_content=False.

Constructor reference

Parameter	Type	Default	Description
`tracer_provider`	`TracerProvider \| None`	Global provider	OpenTelemetry TracerProvider
`capture_content`	`bool`	`True`	Include message/tool content in spans
`agent_name`	`str \| None`	`"unknown"`	Agent name for span attributes
`provider_name`	`str \| None`	`None`	Provider override (auto-detected if unset)
`model_name`	`str \| None`	`None`	Model override (auto-detected if unset)

Show full SKILL.md (217 more words)Show less

Backend integration

TelemetryMiddleware uses standard OpenTelemetry, so any OTLP-compatible backend works:

Jaeger — OTLPSpanExporter(endpoint="http://localhost:4318/v1/traces")
Grafana Tempo — same OTLP exporter, point at the Tempo gateway
Langfuse, Honeycomb, Datadog — vendor-specific exporters; the agent-side setup is identical

For container-orchestrated stacks, this repo includes a tracing/ directory with Docker-Compose for otel-collector + Grafana Tempo.

Going deeper

website/docs/beta/telemetry.mdx — full attribute table, configuration, example.
tracing/ — Docker setup for local otel-collector + Tempo + Grafana.
For sibling middleware (logging, retry, history limits), see ag2-middleware.

Common pitfalls

SimpleSpanProcessor + ConsoleSpanExporter in production — synchronous, blocks every span emit. Use BatchSpanProcessor and a real exporter (OTLP / Jaeger / vendor) outside of dev.
Leaking content into telemetry — capture_content=True is the default. For privacy-sensitive prompts (PII, credentials), set capture_content=False and audit what your backend retains.
Forgetting trace.set_tracer_provider(...) — without it, tracer_provider you pass to the middleware is fine, but third-party libraries that auto-instrument may use a different provider.
Token usage missing — gen_ai.usage.* requires the provider client to surface usage in the response. Streaming providers may emit usage only at the end; if you don't see them, check the provider's response shape.
Span hierarchy doesn't show parent-child — your exporter or backend may need the OTLP/HTTP path enabled, not just OTLP/gRPC. Check both.
Comparing to V1 tracing docs — the semantic-attribute format is the same; only the agent instrumentation method differs (V1 uses instrument_agent() / instrument_llm_wrapper() / instrument_pattern(); beta uses TelemetryMiddleware).

Files

Just SKILL.md in .agents/skills/ag2-telemetry of ag2ai/build-with-ag2.

Open the folder on GitHubat commit 29eeac3

Compare with similar skills

Ag2 Telemetry 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.

Ag2 Telemetry compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Ag2 Telemetry this skillag2ai/build-with-ag2	252	—	~1.9k	Automated safety check: Pass	Apache-2.0	1 mo ago
Observability Architecturemajiayu000/litellm-rs	117	—	~1.3k	Automated safety check: Pass	MIT	today
Frontmcp Observabilityagentfront/frontmcp	146	—	~4.6k	Automated safety check: Pass	Apache-2.0	yesterday
Monitoring Observabilityahmedasmar/devops-claude-skills	203	—	~3.9k	Automated safety check: Pass	None	6 mo ago
App Observabilitygrafana/skills	279	—	~1.8k	Automated safety check: Pass	Apache-2.0	2 days ago
Monitoring Observabilityyonatangross/orchestkit	289	—	~2.2k	Automated safety check: Pass	MIT	yesterday

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Ag2 Use Builtin Tools
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Ag2 Knowledge And Memory
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Ag2 Observers And Alerts
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Auto-check: notes

Works with

Questions about Ag2 Telemetry

What does Ag2 Telemetry do?

Add OpenTelemetry traces to an AG2 beta Agent via TelemetryMiddleware (autogen.beta.middleware.builtin). Ag2 Telemetry is an agent skill from ag2ai/build-with-ag2.builtin).

When should I use Ag2 Telemetry?

Ag2 Telemetry fits situations like: the user wants production-grade traces; latency analysis; token-usage attribution; ship telemetry into an existing observability stack.

How do I install Ag2 Telemetry in Claude Code?

Run `npx skills add ag2ai/build-with-ag2 --skill ag2-telemetry -a claude-code`. Or copy the skill folder (.agents/skills/ag2-telemetry in ag2ai/build-with-ag2) into .claude/skills/ag2-telemetry in your project. Claude Code loads it when a task matches its description.

How do I install Ag2 Telemetry in Codex?

Run `npx skills add ag2ai/build-with-ag2 --skill ag2-telemetry -a codex`. Or copy the skill folder (.agents/skills/ag2-telemetry in ag2ai/build-with-ag2) into .agents/skills/ag2-telemetry in your project. Codex loads it when a task matches its description.

Can I use Ag2 Telemetry 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 ag2ai/build-with-ag2 --skill ag2-telemetry -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ag2-telemetry, .gemini/skills/ag2-telemetry, .github/skills/ag2-telemetry and .opencode/skills/ag2-telemetry in your project.

What does Ag2 Telemetry need to run?

Going by SKILL.md and its folder, Ag2 Telemetry needs the command-line tools its instructions call (pip). Our summary lists: Python 3; Docker.

Does Ag2 Telemetry access the network?

SKILL.md names 1 domain. As links in the text: opentelemetry.io. This is read from the text; nothing was executed.

Is Ag2 Telemetry 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 Ag2 Telemetry use?

Ag2 Telemetry is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Ag2 Telemetry use?

About 1.9k tokens (SKILL.md is roughly 7.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Ag2 Telemetry?

Skills that share tags, products or a category with Ag2 Telemetry: Observability Architecture (majiayu000/litellm-rs, 117 stars), Frontmcp Observability (agentfront/frontmcp, 146 stars), Monitoring Observability (ahmedasmar/devops-claude-skills, 203 stars) and App Observability (grafana/skills, 279 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ag2 Telemetry?

ag2ai (a GitHub organization) maintains it in ag2ai/build-with-ag2, which has 252 GitHub stars. The repository holds 16 skills in this directory. The repository was last updated on September 6, 2026.

Source: ag2ai/build-with-ag2 on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Ag2 Telemetry

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Telemetry — OpenTelemetry instrumentation

When to use

Installation

60-second recipe

Span hierarchy

Span types

Semantic attributes (GenAI semconv)

Content capture (default ON)

Constructor reference

Backend integration

Going deeper

Common pitfalls

Files

Compare with similar skills

Similar skills

More from ag2ai/build-with-ag2

Related

Questions about Ag2 Telemetry