configuring-experiment-analytics

A workflow for configuring the measurement side of a PostHog experiment. An experiment compares versions of a product using user exposure and metrics such as counts, sums, ratios, or retention.

In plain words
What is it for?
Setting exposure events, primary and secondary metrics, metric types, calculation details, retention windows, and multivariate user handling.
Why use it?
It helps ensure the experiment measures the right users and outcomes, including how users assigned to multiple variants are handled.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/posthog/ai-plugin/configuring-experiment-analytics
Any agent
npx skills add PostHog/ai-plugin --skill configuring-experiment-analytics
Clone the repo
git clone --depth 1 https://github.com/PostHog/ai-plugin

Made for: Claude Code, Codex.

Per session 222 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,931 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00222 $0.02931
Opus 5 $0.00111 $0.01465
Sonnet 5 $0.00044 $0.00586
Haiku 4.5 $0.00022 $0.00293

Measured 2d ago against content hash 0412e451c462, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

configuring-experiment-analytics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/configuring-experiment-analytics/SKILL.md · 197 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 197 lines · 222 tokens per session scan A 0412e451c462

Subscribe to this mod's changes

configuring-experiment-analytics is a skill published in the GitHub repository PostHog/ai-plugin (79 stars, last pushed 3d ago), with no licence file. It adds 222 tokens to every session and 2,931 once invoked, about $0.0011 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

domscribe

Work with Domscribe — the pixel-to-code bridge. Use when setting up, initializing, or configuring Domscribe for a project, OR when editing or modifying UI components (React, Vue, Next.js, Nuxt), implementing features from captured UI annotations, querying runtime context for source locations, exploring component…

patchorbit/domscribe · 94 tokens

nowledge-mem-docker

Install, check on, or upgrade a self-hosted Nowledge Mem server (the headless Docker deployment) using the nmemctl lifecycle controller. Use this whenever the user mentions running their own Nowledge Mem instance, self-hosting Mem on a NAS, VPS, homelab, or server, deploying nowledgelabs/mem from Docker Hub…

nowledge-co/community · 183 tokens

nowledge-mem-openclaw-plugin

Use this guide when an AI agent is helping a user install, configure, verify, or explain the Nowledge Mem OpenClaw plugin.

nowledge-co/community · 0 tokens

read-working-memory

Read your daily Working Memory briefing to understand current context. Contains active focus areas, priorities, unresolved flags, and recent knowledge changes. Load this automatically at the beginning of sessions for cross-tool continuity.

nowledge-co/community · 43 tokens

save-thread

Deprecated compatibility skill. In portable Agent Plugins environments this must degrade honestly to a resumable handoff, because real transcript-backed thread import is not guaranteed. Prefer save-handoff here, and use native connectors when you need actual session capture.

nowledge-co/community · 50 tokens

nowledge-mem-guide

Cross-AI personal knowledge graph memory (Nowledge Mem). Stores memories from this tool, Claude Code, Cursor, browser capture, imported documents, and more. Use when: (1) the user asks about prior work, decisions, preferences, people, dates, plans, or todos, (2) the user references something discussed before or says…

nowledge-co/community · 147 tokens