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.
npx skills add PostHog/posthog-foss --skill creating-experimentsgit clone --depth 1 https://github.com/PostHog/posthog-fossWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/posthog/posthog-foss/creating-experiments)<a href="https://agentmods.dev/skills/posthog/posthog-foss/creating-experiments"><img src="https://agentmods.dev/badge/skills/posthog/posthog-foss/creating-experiments/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/posthog/posthog-foss/creating-experiments"><img src="https://agentmods.dev/badge/skills/posthog/posthog-foss/creating-experiments.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00096 | $0.01260 |
| Opus 5 | $0.00048 | $0.00630 |
| Sonnet 5 | $0.00019 | $0.00252 |
| Haiku 4.5 | $0.00010 | $0.00126 |
Grade A, and why
creating-experiments 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Creating experiments
This skill walks through the 3-step flow for creating a new A/B test experiment.
Core principle: draft first, iterate on details
Create the experiment as a draft quickly, then iterate on metrics and configuration. The user gets a tangible draft immediately and can refine it.
The 3-step creation flow
Step 1: What are we testing?
Gather these before calling experiment-create:
- Experiment name — descriptive, inferred from context when possible
- Hypothesis — what you expect to happen (goes in
description) - Feature flag key — kebab-case. Ask if they want a new flag or to reuse an existing one. The flag is auto-created — do NOT create one separately.
- Type — leave empty (will internally default to
"product". The"web"value is reserved for no-code experiments configured visually with the PostHog toolbar in a browser; it cannot be meaningfully driven via MCP. If a user asks for a no-code/toolbar experiment, point them to the PostHog UI instead of creating one here.)
If the user gives enough context to infer these, don't ask — just proceed.
Step 2: Who sees what variant?
This is about rollout configuration.
Before asking any rollout question, load configuring-experiment-rollout. The disambiguation wording, recommendations, and post-answer branches live there — do not formulate rollout questions yourself, and do not assume an example you remember covers the user's path.
Key decision points (covered in detail by configuring-experiment-rollout):
- Variant split (how many variants, what percentage each)
- Overall rollout percentage (what % of all users enter the experiment)
- Whether to persist the flag across authentication steps
If the user doesn't mention rollout specifics, use defaults: 50/50 control/test, 100% rollout.
Step 3: How to measure impact?
This is about analytics and metrics. Load the configuring-experiment-analytics skill for guidance.
That skill's first step checks for an existing shared metric to reuse before building a new one —
don't duplicate a metric the project already has set up.
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.
- 9d ago First seen · 109 lines · 96 tokens per session scan A e513651cdc65
creating-experiments is a skill published in the GitHub repository PostHog/posthog-foss (715 stars, last pushed today), licensed MIT. It adds 96 tokens to every session and 1,260 once invoked, about $0.0005 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 2026-09-03.
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