Agent skill

Experimentation

by andreaskelm in andreaskelm/pm-brain

Design and run product experiments at a practical PM level — A/B tests, hypothesis tests, rollouts, feature flags, and reading results without pretending to be a statistician.

Custom licenceAuto-check passedMarketing & SEO

Install Experimentation

skills CLI
$ npx skills add andreaskelm/pm-brain --skill experimentation -a claude-code

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

GitHub CLI
$ gh skill install andreaskelm/pm-brain experimentation --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/andreaskelm/pm-brain.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/experimentation .claude/skills/experimentation && 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/

Facts

Skill name
experimentation
GitHub stars
234
Token cost
~2.3k tokens
SKILL.md length
1,309 words
Files
3 (incl. references)
Skills in repo
18
Repo updated
First seen
Licence
Custom licence

At a glance

Design and run product experiments at a practical PM level — A/B tests, hypothesis tests, rollouts, feature flags, and reading results without pretending to be a statistician.

  • Works in 6 steps: Preflight (before any design doc) → Lock the hypothesis and the primary metric → Sample, duration, and practical power → …
  • The user says A/B test
  • SKILL.md covers Is this the right thing?, Step 1 — Preflight (before any…, Step 2 — Lock the hypothesis… and Step 3 — Sample, duration, and…, plus 7 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Experimentation is an agent skill from andreaskelm/pm-brain. Design and run product experiments at a practical PM level — A/B tests, hypothesis tests, rollouts, feature flags, and reading results without pretending to be a statistician. Covers hypothesis, primary metric, sample and duration, guardrails, and ship/kill/pivot calls. Use when the user says "A/B test", "experiment design", "hypothesis test", "rollout plan", "feature flag", "statistical significance", "how long should we run this", "can we ship the variant", or needs to decide whether a change actually worked.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/criteria.md` and `references/design.md`).

It sits in Marketing & SEO, covering A/B testing, Statistics and Feature launches and release readiness. The repository describes itself as: AI-powered product management thinking & operating system. Playbooks, guides, templates, and frameworks that bridge PM theory to daily execution.

When your agent uses it

  • The user says A/B test
  • Experiment design
  • Hypothesis test
  • Statistical significance

Example prompts

  • “A/B test”
  • “experiment design”
  • “hypothesis test”
  • “/experimentation”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Preflight (before any design doc)
  2. Lock the hypothesis and the primary metric
  3. Sample, duration, and practical power
  4. Guardrails and secondary metrics
  5. Rollout, feature flags, and operational hygiene
  6. Ship, kill, or pivot (before results arrive)

What it can do on your machine

Read from SKILL.md and the folder at commit 38696ac. 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

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    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

Experimentation loads about 2.3k tokens when it runs, and up to ~3.7k if it reads all its reference files. Until then it costs about 133 tokens; SKILL.md has 1,309 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~133
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.7k

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

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 1,309 words (~2,334 tokens).

“An experiment is how you stop arguing about opinions and start arguing about evidence — but only if you decided what would convince you before the numbers land. The failure mode I see most: someone runs a test because "we…”

— opening of SKILL.md by andreaskelm, Custom licence
name
experimentation

Read the full SKILL.md on GitHub

Files

SKILL.md and 2 other files (references) in .claude/skills/experimentation of andreaskelm/pm-brain.

  • SKILL.md
  • references/criteria.md
  • references/design.md

Open the folder on GitHubat commit 38696ac

Compare with similar skills

Experimentation 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.

Experimentation compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Experimentation this skillandreaskelm/pm-brain234—~2.3kAutomated safety check: PassCustom licence
Ab Test Analysisnimrodfisher/data-analytics-skills470—~708Automated safety check: PassMIT
Measure Experiment Resultsproduct-on-purpose/pm-skills716—~989Automated safety check: PassApache-2.0
Experimentai-analyst-lab/ai-analyst304—~2kAutomated safety check: PassMIT
Mkt Experimentevolution-foundation/evo-nexus545—~1.2kAutomated safety check: PassCustom licence
A/B Test Analysisphuryn/pm-skills27k—~893Automated safety check: PassMIT

Similar skills

  • Ab Test Analysis

    nimrodfisher/data-analytics-skills

    Rigorous A/B test statistical analysis. An agent skill from nimrodfisher/data-analytics-skills.

    470 GitHub stars~708 tokensUpdated 15 days ago
    Marketing & SEOAuto-check passed
  • Measure Experiment Results

    product-on-purpose/pm-skills

    Documents the results of a completed experiment or A/B test with statistical analysis, learnings, and recommendations.

    716 GitHub stars~989 tokensUpdated 2 days ago
    Marketing & SEOAuto-check passed
  • Experiment

    ai-analyst-lab/ai-analyst

    The analysis and lifecycle owner for experiments. An agent skill from ai-analyst-lab/ai-analyst.

    304 GitHub stars~2k tokensUpdated 9 days ago
    Marketing & SEOAuto-check passed
  • Mkt Experiment

    evolution-foundation/evo-nexus

    Autonomous growth experimentation framework. An agent skill from evolution-foundation/evo-nexus.

    545 GitHub stars~1.2k tokensUpdated 4 mo ago
    Marketing & SEOAuto-check passed
  • A/B Test Analysis

    phuryn/pm-skills

    Validates an experiment's setup, works out lift, p-value and confidence interval from A/B test data, and recommends whether to ship, extend or stop.

    27k GitHub stars~893 tokensUpdated today
    Data & AnalyticsAuto-check passed
  • Statistical Analyst

    alirezarezvani/claude-skills

    Run hypothesis tests, analyze A/B experiment results, calculate sample sizes, and interpret statistical significance with effect sizes.

    28k GitHub stars~2.5k tokensUpdated 1 mo ago
    Data & AnalyticsAuto-check passed

More from andreaskelm/pm-brain

All 18 skills in this repo
  • AI Product Management

    andreaskelm/pm-brain

    Ship and spec AI features, LLM products, agents, copilots, and generative UX — including when to use a model vs.

    234 GitHub stars~1.8k tokensUpdated yesterday
    Auto-check passed
  • Discovery Synthesis

    andreaskelm/pm-brain

    Plan customer discovery, turn interview snapshots into synthesis and evidence-based opportunities, build or update an Opportunity Solution Tree, map jobs and segments, and design RAT tests for the…

    234 GitHub stars~2.3k tokensUpdated yesterday
    Auto-check passed
  • Eng Design Collab

    andreaskelm/pm-brain

    Partner effectively with engineering and design — feasibility and scope negotiation, tech debt tradeoffs, design reviews, discovery with builders, and PRD handoffs that don't get thrown away.

    234 GitHub stars~2.1k tokensUpdated yesterday
    Auto-check passed
  • Launch Gtm

    andreaskelm/pm-brain

    Plan, tighten, or review a product launch and go-to-market motion: rollout phases, beta and GA readiness, sales enablement, marketing launch, and release comms (internal and external).

    234 GitHub stars~2.1k tokensUpdated yesterday
    Auto-check passed
  • North Star

    andreaskelm/pm-brain

    Define, sharpen, or audit a North Star metric and its input metrics tree, and decide which product metrics actually matter (leading vs.

    234 GitHub stars~2.5k tokensUpdated yesterday
    Auto-check passed
  • Okr

    andreaskelm/pm-brain

    Write, draft, review, or fix OKRs (objectives and key results) for a team, product area, or quarter, and run weekly confidence check-ins, mid-cycle adjustments, and end-of-cycle grading.

    234 GitHub stars~2.5k tokensUpdated yesterday
    Auto-check passed

Questions about Experimentation

What does Experimentation do?

Design and run product experiments at a practical PM level — A/B tests, hypothesis tests, rollouts, feature flags, and reading results without pretending to be a statistician. Experimentation is an agent skill from andreaskelm/pm-brain. Design and run product experiments at a practical PM level — A/B tests, hypothesis tests, rollouts, feature flags, and reading results without pretending to be a statistician.

When should I use Experimentation?

Experimentation fits situations like: the user says A/B test; experiment design; hypothesis test; statistical significance.

How do I install Experimentation in Claude Code?

Run `npx skills add andreaskelm/pm-brain --skill experimentation -a claude-code`. Or copy the skill folder (.claude/skills/experimentation in andreaskelm/pm-brain) into .claude/skills/experimentation in your project. Claude Code loads it when a task matches its description.

How do I install Experimentation in Codex?

Run `npx skills add andreaskelm/pm-brain --skill experimentation -a codex`. Or copy the skill folder (.claude/skills/experimentation in andreaskelm/pm-brain) into .agents/skills/experimentation in your project. Codex loads it when a task matches its description.

Can I use Experimentation 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 andreaskelm/pm-brain --skill experimentation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/experimentation, .gemini/skills/experimentation, .github/skills/experimentation and .opencode/skills/experimentation in your project.

What does Experimentation need to run?

SKILL.md names no scripts, command-line tools or credentials: Experimentation is instructions for the agent only.

Does Experimentation access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Experimentation 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 Experimentation use?

Experimentation has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Experimentation use?

About 2.3k tokens (SKILL.md is roughly 9.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.3k tokens, read only when the agent opens those files.

What are the alternatives to Experimentation?

Skills that share tags, products or a category with Experimentation: Ab Test Analysis (nimrodfisher/data-analytics-skills, 470 stars), Measure Experiment Results (product-on-purpose/pm-skills, 716 stars), Experiment (ai-analyst-lab/ai-analyst, 304 stars) and Mkt Experiment (evolution-foundation/evo-nexus, 545 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Experimentation?

andreaskelm (a GitHub user) maintains it in andreaskelm/pm-brain, which has 234 GitHub stars. The repository holds 18 skills in this directory. The repository was last updated on October 9, 2026.

Source: andreaskelm/pm-brain on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.