Instrument Metrics

PostHogOfficialCreated by PostHog

Skill
Tool integration
Data and AI
MIT
Low risk

From the author

Add PostHog metric capture to track counters, gauges, and histograms. Use after implementing features or reviewing PRs to ensure key operations are measured, or when asked to add metrics, counters, or track a value over time. Also handles mirroring existing Prometheus/StatsD/OpenTelemetry metrics into PostHog and initial OTLP exporter setup.

— the description by PostHog

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured approach to instrumenting applications with PostHog metrics. It supports various platforms including Web, Node.js, Python, and Kubernetes, and offers a path for integrating existing OpenTelemetry setups. The skill emphasizes non-intrusive instrumentation, advising developers to add PostHog calls alongside existing metrics rather than replacing them. It includes guidance on selecting appropriate metric types, maintaining low cardinality for performance, and configuring environment variables securely.

What it does

Detects existing metrics instrumentation and platform-specific requirements.
Implements PostHog metric capture for counters, gauges, and histograms.
Mirrors existing Prometheus, StatsD, or OpenTelemetry metrics into PostHog.
Configures OTLP exporters for applications already using OpenTelemetry.
Provides guidance on setting up necessary environment variables for authentication.
Ensures metrics are correctly flushed in short-lived processes.

When to use it

After implementing new features that require performance or usage tracking.
When asked to add specific counters or gauges to an existing codebase.
When you need to track values over time, such as queue depths or API durations.
When migrating or mirroring existing metrics from other providers into PostHog.
When you need to set up initial OTLP exporter configurations.

Advantages

Non-destructive: adds metrics alongside existing instrumentation without restructuring code.
Flexible: supports native SDKs and standard OpenTelemetry protocols.
Performance-conscious: provides clear rules on maintaining low cardinality to prevent series explosion.
Secure: mandates the use of environment variables for sensitive configuration keys.
Robust: includes error handling guidelines to ensure metrics collection does not break application boot.

Usage examples

“Add a counter to track the number of successful user signups in my Python application.”: The agent will analyze the Python environment, identify the appropriate PostHog SDK or OTLP setup, and insert a counter increment call at the successful signup logic point.
“Mirror my existing Prometheus metrics into PostHog.”: The agent will identify the existing OTLP exporter or Prometheus client, configure the endpoint to point to PostHog, and ensure the project token is correctly set via environment variables.

Install

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/posthog/instrument-metrics/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip instrument-metrics.zip -d .agents/skills

Documentation by PostHog

Add PostHog metric capture

Use this skill to add PostHog metric capture (counters, gauges, and histograms) for new or changed code. Use it after implementing features or reviewing PRs to ensure key operations are measured, when the user asks to add metrics or counters, or to mirror existing metrics instrumentation into PostHog. Supports any platform or language.

Supported platforms: Web (JavaScript), Node.js, Python via the posthog.metrics SDK API, Kubernetes via the metrics agent, and any language via OpenTelemetry (OTLP).

Instructions

Follow these steps IN ORDER:

STEP 1: Analyze the codebase and detect the platform.

Detect the language, framework, and existing metrics setup.
Look for dependency files and project files (package.json, requirements.txt, pyproject.toml, go.mod, pom.xml, etc.).
Look for existing metrics instrumentation: Prometheus clients (prom-client, prometheus_client), StatsD/Datadog clients, OpenTelemetry meters, or an OpenTelemetry Collector config.
Check whether a PostHog SDK (posthog-js, posthog-node, posthog-python) is already installed.

STEP 2: Choose the capture path.

If a PostHog SDK is installed (or the platform supports one), use the posthog.metrics API — no OpenTelemetry packages needed. Read the matching platform reference now.
If the codebase already exports OpenTelemetry metrics, point the existing OTLP metrics exporter (or Collector) at PostHog instead — read the "Other Languages" reference. No application code changes needed beyond exporter config.
If neither applies, use the "Other Languages" reference as a fallback — it covers the generic OpenTelemetry approach.

STEP 3: Instrument alongside existing metrics.

Where the codebase already records a metric (a Prometheus counter, a StatsD call, an OTel instrument), add the PostHog call next to the existing one, reusing the same metric name and attributes. Do NOT remove or restructure the existing instrumentation.
Do not alter the fundamental architecture of existing files. Make additions minimal and targeted.
You must read a file immediately before attempting to write it.

STEP 4: Add new metrics where they belong.

Where the user asked for new metrics, or key operations have no coverage, add PostHog metric calls at the sites they belong: count successes and failures of critical flows, time external calls and jobs with histograms, gauge queue depths and pool sizes.
Pick the right type: counters for things that only go up, gauges for values that go up and down, histograms for distributions like durations. Set an explicit unit on histograms (ms, bytes).
Use stable, descriptive, dot-separated names (jobs.processed, api.request.duration) and set a service name so systems stay easy to tell apart.

STEP 5: Keep cardinality low.

Attributes like route, status, plan, or queue are good; user IDs, session IDs, request IDs, and timestamps are not. Every unique attribute combination creates a new series.
If something needs per-user or per-request detail, that's a job for PostHog logs or traces, not metrics.

STEP 6: Set up environment variables. (Skip if the PostHog SDK is already configured — posthog.metrics reuses the SDK's existing project token.)

Check if the project already has PostHog environment variables configured (e.g. in .env, .env.local, or framework-specific env files). If valid values already exist, skip this step.
If the PostHog project token is missing, use the PostHog MCP server's projects-get tool to retrieve the project's api_token. If multiple projects are returned, ask the user which project to use. If the MCP server is not connected or not authenticated, ask the user for their PostHog project token instead.
For the PostHog host URL: check the projects-get MCP response for a region field — US maps to https://us.i.posthog.com, EU maps to https://eu.i.posthog.com. If the region is not available from the MCP response or from existing project configuration, ask the user: "Are you on PostHog US Cloud or EU Cloud?" Do not assume US Cloud.
For the OTLP metrics endpoint, use https://us.i.posthog.com/i/v1/metrics (US) or https://eu.i.posthog.com/i/v1/metrics (EU), matching the region determined above, with the project token as an Authorization: Bearer header.
Write these values to the appropriate env file using the framework's naming convention.
Reference these environment variables in code instead of hardcoding them.

STEP 7: Verify metrics arrive.

For short-lived processes (scripts, cron jobs, serverless), flush before exit (posthog.metrics.flush(), or the OTel provider's forceFlush()/shutdown()).
Open Metrics in the PostHog sidebar and pick the metric from the name picker; data points should appear within a minute of sending.

Reference files

references/javascript.md - JavaScript (web) metrics installation
references/nodejs.md - Node.js metrics installation
references/python.md - Python metrics installation
references/kubernetes.md - Kubernetes metrics installation
references/other.md - Other languages metrics installation
references/start-here.md - Getting started with metrics
references/basics.md - Why you need metrics
references/architecture.md - How metrics works
references/COMMANDMENTS.md - Framework-specific rules the integration must follow

Each platform reference contains specific SDK setup, OTLP configuration, and integration patterns. Find the one matching the user's stack.

Key principles

Environment variables: Always use environment variables for PostHog keys and OpenTelemetry endpoints. Never hardcode them.
Minimal changes: Add PostHog metric capture alongside existing metrics. Don't replace or restructure existing instrumentation.
Prefer the SDK: When a PostHog SDK is present, posthog.metrics needs no new packages and no extra authentication. Reserve OTLP setup for codebases already invested in OpenTelemetry or languages without SDK support.
Low cardinality: Every unique attribute combination creates a new series. Attach bounded dimensions like route, status, or plan — never user IDs, session IDs, or request IDs.

Files

ATTRIBUTION.mdAdded by AutoGineer940 B
LICENSELicence file added by AutoGineer1.0 KiB
SKILL.md6.5 KiB
references/COMMANDMENTS.md1.5 KiB
references/architecture.md7.0 KiB
references/basics.md5.4 KiB
references/javascript.md4.4 KiB
references/kubernetes.md9.0 KiB
references/nodejs.md4.6 KiB
references/other.md4.5 KiB
references/python.md4.5 KiB
references/start-here.md6.6 KiB

references/python.md

AI agents: this is one page from PostHog's docs. Full index of Markdown docs for LLMs: https://posthog.com/llms.txt

Python metrics installation

Canonical URL: https://posthog.com/docs/metrics/installation/python

Cloud region: This page uses US Cloud hosts. For an EU Cloud project, use https://eu.i.posthog.com instead of https://us.i.posthog.com (ingestion host), and use https://eu.posthog.com instead of https://app.posthog.com (app host for links).

1
Install posthog-python
Required
```
pip install posthog
```
Metrics requires an up-to-date SDK version, so upgrade if you're on an older release.
2
Initialize the client
Required
Set a service name so metrics from different systems stay easy to tell apart. It's attached to every series and used by the Metrics UI for filtering.
```
from posthog import Posthog

posthog = Posthog(
    "<ph_project_token>",
    host="https://us.i.posthog.com",
    metrics={"service_name": "billing-worker"},
)
```
Use your project token (the same one you use for capturing events), not a personal API key.
3
Record metrics
Required
Use the metric type that matches what you're measuring:
```
# Counters only go up: things you count
posthog.metrics.count("invoices.processed", 1, attributes={"plan": "pro"})

# Gauges go up and down: current values
posthog.metrics.gauge("queue.depth", 42)

# Histograms record distributions: durations, sizes
posthog.metrics.histogram("job.duration", 187, unit="ms")
```
The client is thread-safe and pre-aggregates: samples fold into per-series aggregates in memory and flush as one OTLP data point per series every few seconds, so recording in hot paths is cheap. A burst of 10k count() calls costs one data point on the wire.
Keep attribute values small and bounded: route, status, and plan are good attributes; user IDs, session IDs, and request IDs are not. Every unique combination creates a new series.
4
Instrument alongside existing metrics
Optional
If your service already records metrics with Prometheus, StatsD, or another system, don't rip it out. Add the PostHog call next to the existing one, reusing the same metric name and attributes, so both systems chart the same series while you evaluate.
5
Flush before exit
Required
For short-lived processes (cron jobs, CLIs, serverless functions), flush before exiting so the last aggregation window isn't lost:
```
posthog.metrics.flush()
```
6
Test your setup
Recommended
1. Trigger the code path that records a metric
2. Open Metrics in the PostHog sidebar and pick your metric from the name picker
3. Data points should appear within a minute of sending
View your metrics in PostHog

Next steps

Checkpoint

What you can do with your metrics

Action	Description
Why you need metrics	What metrics show you that events and logs don't
Getting started guide	Pick the right metric type, add attributes carefully, and chart what matters
Group and filter	Group by an attribute for one line per value, or filter with `key=value` chips
How metrics works	How metrics are ingested, stored, and queried
Query with SQL	Every metric lands in the `posthog.metrics` table, queryable from the SQL tab

Continue with the getting started guide

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an MCP server, Needs Python, Needs Node.js

Security

What our scanner noticed· Low risk

Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by

PostHog

Publisher

PostHog (Official)

Source

PostHog/skills · skills/omnibus/instrument-metrics · commit a5d30e7

Licence

MIT License (redistribution allowed)

LICENSE (added by AutoGineer from LICENSE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-08

AutoGineer is not affiliated with or endorsed by PostHog.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download instrument-metrics.zip

From the author

AutoGineer summary

What it does

When to use it

Advantages

Usage examples

Install

Documentation by PostHog

Add PostHog metric capture

Instructions

Reference files

Key principles

Files

references/python.md

Python metrics installation

On this page

Install posthog-python

Initialize the client

Record metrics

Instrument alongside existing metrics

Flush before exit

Test your setup

Next steps

Requirements and compatibility

Security

Attribution and licence

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Download ZIP