$ ~/registry/skill/microsoft-github-skills-experimental-copilot-otel-metrics

SKILL

copilot-otel-metrics

Set up Copilot OpenTelemetry capture, backend, and dashboards.

Source

GitHub

Updated

2026-08-21

// securityLow risk

Prompt only, no code
Open source

Running security audit…

Credentials
Network egress
Code execution
Data access
Supply chain

// install

Copy the install command and let the AI configure it · recommended for beginners

Please install the "copilot-otel-metrics" skill from askskill:
1. Download https://raw.githubusercontent.com/microsoft/hve-core/main/.github/skills/experimental/copilot-otel-metrics/SKILL.md
2. Save it as ~/.claude/skills/copilot-otel-metrics/SKILL.md
3. Reload skills and tell me it's ready

// download

Download SKILL.mdInstall manifest ↗

// examples

Enable local capture

Prompt

Help me enable GitHub Copilot OpenTelemetry export on this machine. First show the VS Code settings diff, then generate the configuration to write after approval.

Expected

A settings diff showing what will change and what can be written after approval.

Create a local Grafana stack

Prompt

Generate a local Grafana stack and dashboard for Copilot telemetry, and give me the commands to run manually. Do not execute them for me.

Expected

Local backend files, a dashboard, and manual run commands.

Prepare an organization Azure setup

Prompt

Prepare Azure collector, infrastructure, and dashboard templates for organization-wide Copilot telemetry, and explain what must be confirmed before deployment.

Expected

Deployable Azure templates plus pre-deployment guidance.

// use cases

Debug Copilot metrics on one machine

A developer wants to verify Copilot OTel export on their own machine first. This mode shows the settings diff and writes configuration only after approval.

View metrics in a local dashboard

When export is enabled and you want a local backend to receive and query the data, this mode generates a local Grafana stack and dashboard. It writes files but does not run services for you.

Deploy an Azure telemetry pipeline for a team

Ops or platform teams can use this to centralize a group’s Copilot metrics in Azure and chart them. It generates collector, infrastructure, and dashboard templates and highlights what must be confirmed before deployment.

// docs

AI summary

This document explains the goal, modes, and workflow for Copilot OpenTelemetry metrics. It covers enabling VS Code export, generating a local Grafana stack and dashboard, drafting organization-wide distribution configs, or producing Azure capture templates. It emphasizes choosing the right mode, reading the relevant reference, obtaining approval before automation, and verifying success by querying the backend rather than trusting an HTTP status.

Show full docs ▾

Copilot OpenTelemetry Metrics

Goal

Take the user from "I want Copilot telemetry" to telemetry they can query. Do the work for them where doing it is safe and reversible, and walk them through it where it is not.

Done means export is enabled in the settings file that actually resolves, a backend is receiving data, a dashboard exists for that backend, and the user has confirmed data landed by querying the store rather than by trusting an HTTP 200.

Modes

Modes are independent. A user may run one, several, or all. Local capture and organization capture are separate journeys, not stages of the same one.

Mode	Use when the user wants to	Consent gate	Reference
`local-setup`	Turn on Copilot's OTel export on this machine	Show the exact settings diff and write only after approval	references/local-setup.md
`local-stack`	Get a backend on this machine to receive it	Write the files, then hand over the command; never run it	references/local-stack.md
`org-distribution`	Push OTel settings to a fleet of developers	Nothing is applied; draft the configuration and explain it	references/org-distribution.md
`azure-capture`	Collect a fleet's telemetry into Azure and chart it	Write the templates, then hand over the deploy commands	references/azure-capture.md

references/verification.md is shared by every mode. Read it before telling anyone their telemetry works.

When the request names a goal rather than a mode, pick the mode that reaches the goal and say which one was picked. "Set up Copilot metrics" with no other context means local-setup followed by local-stack. Confirm before assuming the organization path, because it spends money and places a shared write credential on every workstation.

Flow

Pick the mode and state the pick. Ask only when local and organization scope are genuinely ambiguous.
Read that mode's reference before acting. The table above is routing only; the procedure, the failure modes, and the artifact contents live in the reference.
Offer rather than assume. Say what would change, where, and what cannot be undone. Every automated step has a manual equivalent, and a user who declines gets the exact block to paste or the exact command to run.
Write files; do not run them. The agent writes settings after an approved diff, writes generated artifacts to disk, and may run read-only queries against a local telemetry store. Every command that touches Docker, a cloud control plane, or an infrastructure-as-code toolchain belongs to the user: print it and stop.
Verify by querying the store, following the shared verification reference. Report what proved the data landed.
Offer the dashboard. Local capture gets a generated PromQL dashboard; the Azure path gets a generated KQL dashboard. They target different backends and are not interchangeable.

Content capture is not governed by the content-capture setting

Raise this before anyone enables export, in every mode.

github.copilot.chat.otel.captureContent defaults to false and is documented as controlling whether input and output messages, system instructions, and tool definitions reach span attributes. A false value does not mean the store holds no prompt text. With that setting disabled, this stack observed six attributes populated in plaintext on spans:

…

View full docs ↗

// FAQ

What does this skill do?

It helps you turn GitHub Copilot OpenTelemetry metrics from “wanted” into “queryable.” It covers local export, a local Grafana stack, and an organization-level Azure capture path.

Will it deploy to production for me?

No. The docs say it writes files, generates templates, and hands you the commands to run; it does not execute the local stack for you.

How do I confirm telemetry actually works?

You should confirm by querying the storage backend to see landed data, not by trusting an HTTP 200. The shared verification steps are documented separately.