Analytics
Nexus-JPF/note-companion
When the user wants to set up, improve, or audit analytics tracking and measurement.
When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program.
Install Ab Testing
$ npx skills add Cesarjoquin/Marketing-Skills --skill ab-testing -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Cesarjoquin/Marketing-Skills ab-testing --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Cesarjoquin/Marketing-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ab-testing .claude/skills/ab-testing && rm -rf skills-srcUse ~/.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/
Install the "ab-testing" agent skill from https://github.com/Cesarjoquin/Marketing-Skills/tree/main/skills/ab-testing into .claude/skills/ab-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ab-testing", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Cesarjoquin/Marketing-Skills/tree/main/skills/ab-testingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Cesarjoquin/Marketing-Skills --skill ab-testing -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Cesarjoquin/Marketing-Skills ab-testing --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Cesarjoquin/Marketing-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ab-testing .agents/skills/ab-testing && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ab-testing" agent skill from https://github.com/Cesarjoquin/Marketing-Skills/tree/main/skills/ab-testing into .agents/skills/ab-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ab-testing", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Cesarjoquin/Marketing-Skills --skill ab-testing -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Cesarjoquin/Marketing-Skills ab-testing --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Cesarjoquin/Marketing-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ab-testing .cursor/skills/ab-testing && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ab-testing" agent skill from https://github.com/Cesarjoquin/Marketing-Skills/tree/main/skills/ab-testing into .cursor/skills/ab-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ab-testing", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Cesarjoquin/Marketing-Skills.git --path skills/ab-testing--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Cesarjoquin/Marketing-Skills --skill ab-testing -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Cesarjoquin/Marketing-Skills ab-testing --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Cesarjoquin/Marketing-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ab-testing .gemini/skills/ab-testing && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ab-testing" agent skill from https://github.com/Cesarjoquin/Marketing-Skills/tree/main/skills/ab-testing into .gemini/skills/ab-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ab-testing", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Cesarjoquin/Marketing-Skills ab-testingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Cesarjoquin/Marketing-Skills --skill ab-testing -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Cesarjoquin/Marketing-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ab-testing .github/skills/ab-testing && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ab-testing" agent skill from https://github.com/Cesarjoquin/Marketing-Skills/tree/main/skills/ab-testing into .github/skills/ab-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ab-testing", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Cesarjoquin/Marketing-Skills --skill ab-testing -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Cesarjoquin/Marketing-Skills ab-testing --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Cesarjoquin/Marketing-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ab-testing .opencode/skills/ab-testing && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ab-testing" agent skill from https://github.com/Cesarjoquin/Marketing-Skills/tree/main/skills/ab-testing into .opencode/skills/ab-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ab-testing", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
ab-testing- GitHub stars
- 199
- Used in
- 2 other repos
- Token cost
- ~2.8k tokens
- SKILL.md length
- 1,108 words
- Files
- 4 (incl. references)
- Skills in repo
- 12
- Repo updated
- First seen
- Licence
- MIT
At a glance
When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program.
- Works in 4 steps: Start with a Hypothesis → Test One Thing → Statistical Rigor → …
- Implement an A/B test
- SKILL.md covers Initial Assessment, Core Principles, Hypothesis Framework and Test Types, plus 7 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Ab Testing is an agent skill from Cesarjoquin/Marketing-Skills. When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program," or "experiment…
Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `evals/evals.json`, `references/sample-size-guide.md` and `references/test-templates.md`).
It sits in Marketing & SEO, covering A/B testing. The repository describes itself as: AI agent Marketing skills for Claude Code and AI agents. CRO, copywriting, SEO, analytics, ai agent, and growth engineering, ai agent. The licence is MIT.
When your agent uses it
- Implement an A/B test
- Build a growth experimentation program
- The user mentions A/B test
- Test this change
Example prompts
- “A/B test,”
- “split test,”
- “experiment,”
- “/ab-testing”
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 23b887f. 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
Links to these hosts (documentation or services it may open):
evanmiller.orgoptimizely.com
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
Ab Testing loads about 2.8k tokens when it runs, and up to ~6.3k if it reads all its reference files. Until then it costs about 199 tokens; SKILL.md has 1,108 words of instructions outside code blocks.
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
The full file from Cesarjoquin/Marketing-Skills at commit 23b887f, republished under its MIT licence (© Cesarjoquin). 1,108 words, ~2,788 tokens.
Download SKILL.mdSave it as
.claude/skills/ab-testing/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- ab-testing
- description
- When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program," or "experiment playbook." Use this whenever someone is comparing two approaches and wants to measure which performs better, or when they want to build a systematic experimentation practice. For tracking implementation, see analytics. For page-level conversion optimization, see cro.
- metadata.version
- 2.0.0
A/B Test Setup
You are an expert in experimentation and A/B testing. Your goal is to help design tests that produce statistically valid, actionable results.
Initial Assessment
Check for product marketing context first:
If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Before designing a test, understand:
- Test Context - What are you trying to improve? What change are you considering?
- Current State - Baseline conversion rate? Current traffic volume?
- Constraints - Technical complexity? Timeline? Tools available?
Core Principles
1. Start with a Hypothesis
- Not just "let's see what happens"
- Specific prediction of outcome
- Based on reasoning or data
2. Test One Thing
- Single variable per test
- Otherwise you don't know what worked
3. Statistical Rigor
- Pre-determine sample size
- Don't peek and stop early
- Commit to the methodology
4. Measure What Matters
- Primary metric tied to business value
- Secondary metrics for context
- Guardrail metrics to prevent harm
Hypothesis Framework
Structure
Because [observation/data],
we believe [change]
will cause [expected outcome]
for [audience].
We'll know this is true when [metrics].Example
Weak: "Changing the button color might increase clicks."
Strong: "Because users report difficulty finding the CTA (per heatmaps and feedback), we believe making the button larger and using contrasting color will increase CTA clicks by 15%+ for new visitors. We'll measure click-through rate from page view to signup start."
Test Types
| Type | Description | Traffic Needed |
|---|---|---|
| A/B | Two versions, single change | Moderate |
| A/B/n | Multiple variants | Higher |
| MVT | Multiple changes in combinations | Very high |
| Split URL | Different URLs for variants | Moderate |
Sample Size
Quick Reference
| Baseline | 10% Lift | 20% Lift | 50% Lift |
|---|---|---|---|
| 1% | 150k/variant | 39k/variant | 6k/variant |
| 3% | 47k/variant | 12k/variant | 2k/variant |
| 5% | 27k/variant | 7k/variant | 1.2k/variant |
| 10% | 12k/variant | 3k/variant | 550/variant |
Calculators:
For detailed sample size tables and duration calculations: See references/sample-size-guide.md
Metrics Selection
Primary Metric
- Single metric that matters most
- Directly tied to hypothesis
- What you'll use to call the test
Secondary Metrics
- Support primary metric interpretation
- Explain why/how the change worked
Guardrail Metrics
- Things that shouldn't get worse
- Stop test if significantly negative
Example: Pricing Page Test
- Primary: Plan selection rate
- Secondary: Time on page, plan distribution
- Guardrail: Support tickets, refund rate
Designing Variants
What to Vary
| Category | Examples |
|---|---|
| Headlines/Copy | Message angle, value prop, specificity, tone |
| Visual Design | Layout, color, images, hierarchy |
| CTA | Button copy, size, placement, number |
| Content | Information included, order, amount, social proof |
Best Practices
- Single, meaningful change
- Bold enough to make a difference
- True to the hypothesis
Traffic Allocation
| Approach | Split | When to Use |
|---|---|---|
| Standard | 50/50 | Default for A/B |
| Conservative | 90/10, 80/20 | Limit risk of bad variant |
| Ramping | Start small, increase | Technical risk mitigation |
Considerations:
- Consistency: Users see same variant on return
- Balanced exposure across time of day/week
Implementation
Client-Side
- JavaScript modifies page after load
- Quick to implement, can cause flicker
- Tools: PostHog, Optimizely, VWO
Server-Side
- Variant determined before render
- No flicker, requires dev work
- Tools: PostHog, LaunchDarkly, Split
Running the Test
Pre-Launch Checklist
- Hypothesis documented
- Primary metric defined
- Sample size calculated
- Variants implemented correctly
- Tracking verified
- QA completed on all variants
During the Test
DO:
- Monitor for technical issues
- Check segment quality
- Document external factors
Avoid:
- Peek at results and stop early
- Make changes to variants
- Add traffic from new sources
The Peeking Problem
Looking at results before reaching sample size and stopping early leads to false positives and wrong decisions. Pre-commit to sample size and trust the process.
Analyzing Results
Statistical Significance
- 95% confidence = p-value < 0.05
- Means <5% chance result is random
- Not a guarantee—just a threshold
Analysis Checklist
- Reach sample size? If not, result is preliminary
- Statistically significant? Check confidence intervals
- Effect size meaningful? Compare to MDE, project impact
- Secondary metrics consistent? Support the primary?
- Guardrail concerns? Anything get worse?
- Segment differences? Mobile vs. desktop? New vs. returning?
Interpreting Results
| Result | Conclusion |
|---|---|
| Significant winner | Implement variant |
| Significant loser | Keep control, learn why |
| No significant difference | Need more traffic or bolder test |
| Mixed signals | Dig deeper, maybe segment |
Show full SKILL.md (453 more words)Show less
Documentation
Document every test with:
- Hypothesis
- Variants (with screenshots)
- Results (sample, metrics, significance)
- Decision and learnings
For templates: See references/test-templates.md
Growth Experimentation Program
Individual tests are valuable. A continuous experimentation program is a compounding asset. This section covers how to run experiments as an ongoing growth engine, not just one-off tests.
The Experiment Loop
1. Generate hypotheses (from data, research, competitors, customer feedback)
2. Prioritize with ICE scoring
3. Design and run the test
4. Analyze results with statistical rigor
5. Promote winners to a playbook
6. Generate new hypotheses from learnings
→ RepeatHypothesis Generation
Feed your experiment backlog from multiple sources:
| Source | What to Look For |
|---|---|
| Analytics | Drop-off points, low-converting pages, underperforming segments |
| Customer research | Pain points, confusion, unmet expectations |
| Competitor analysis | Features, messaging, or UX patterns they use that you don't |
| Support tickets | Recurring questions or complaints about conversion flows |
| Heatmaps/recordings | Where users hesitate, rage-click, or abandon |
| Past experiments | "Significant loser" tests often reveal new angles to try |
ICE Prioritization
Score each hypothesis 1-10 on three dimensions:
| Dimension | Question |
|---|---|
| Impact | If this works, how much will it move the primary metric? |
| Confidence | How sure are we this will work? (Based on data, not gut.) |
| Ease | How fast and cheap can we ship and measure this? |
ICE Score = (Impact + Confidence + Ease) / 3
Run highest-scoring experiments first. Re-score monthly as context changes.
Experiment Velocity
Track your experimentation rate as a leading indicator of growth:
| Metric | Target |
|---|---|
| Experiments launched per month | 4-8 for most teams |
| Win rate | 20-30% is common for mature programs (sustained higher rates may indicate conservative hypotheses) |
| Average test duration | 2-4 weeks |
| Backlog depth | 20+ hypotheses queued |
| Cumulative lift | Compound gains from all winners |
The Experiment Playbook
When a test wins, don't just implement it — document the pattern:
## [Experiment Name]
**Date**: [date]
**Hypothesis**: [the hypothesis]
**Sample size**: [n per variant]
**Result**: [winner/loser/inconclusive] — [primary metric] changed by [X%] (95% CI: [range], p=[value])
**Guardrails**: [any guardrail metrics and their outcomes]
**Segment deltas**: [notable differences by device, segment, or cohort]
**Why it worked/failed**: [analysis]
**Pattern**: [the reusable insight — e.g., "social proof near pricing CTAs increases plan selection"]
**Apply to**: [other pages/flows where this pattern might work]
**Status**: [implemented / parked / needs follow-up test]Over time, your playbook becomes a library of proven growth patterns specific to your product and audience.
Experiment Cadence
Weekly (30 min): Review running experiments for technical issues and guardrail metrics. Don't call winners early — but do stop tests where guardrails are significantly negative.
Bi-weekly: Conclude completed experiments. Analyze results, update playbook, launch next experiment from backlog.
Monthly (1 hour): Review experiment velocity, win rate, cumulative lift. Replenish hypothesis backlog. Re-prioritize with ICE.
Quarterly: Audit the playbook. Which patterns have been applied broadly? Which winning patterns haven't been scaled yet? What areas of the funnel are under-tested?
Common Mistakes
Test Design
- Testing too small a change (undetectable)
- Testing too many things (can't isolate)
- No clear hypothesis
Execution
- Stopping early
- Changing things mid-test
- Not checking implementation
Analysis
- Ignoring confidence intervals
- Cherry-picking segments
- Over-interpreting inconclusive results
Task-Specific Questions
- What's your current conversion rate?
- How much traffic does this page get?
- What change are you considering and why?
- What's the smallest improvement worth detecting?
- What tools do you have for testing?
- Have you tested this area before?
Related Skills
- cro: For generating test ideas based on CRO principles
- analytics: For setting up test measurement
- copywriting: For creating variant copy
© Cesarjoquin, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 3 other files (references) in skills/ab-testing of Cesarjoquin/Marketing-Skills.
- SKILL.md
- evals/evals.json
- references/sample-size-guide.md
- references/test-templates.md
Open the folder on GitHubat commit 23b887f
Used in 2 other repositories
We found 4 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in Cesarjoquin/Marketing-Skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Ab Testing 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Ab Testing this skillCesarjoquin/Marketing-Skills | 199 | 2 repos | ~2.8k | Automated safety check: Pass | MIT | |
| AnalyticsNexus-JPF/note-companion | 869 | 6 repos | ~2.2k | Automated safety check: Pass | MIT | |
| Ab Test Setupfreekmurze/dotfiles | 1k | 15 repos | ~1.8k | Automated safety check: Pass | None | |
| Ad Test Designeraaron-he-zhu/aaron-marketing-skills | 2.9k | 2 repos | ~2.8k | Automated safety check: Pass | Apache-2.0 | |
| Meta Tags Optimizernowork-studio/notfair-plugin | 3.9k | 1 repos | ~2.7k | Automated safety check: Pass | MIT | |
| Ab Test Analyzeririnabuht12-oss/marketing-skills | 3.8k | — | ~1.4k | Automated safety check: Pass | None |
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Related
Categories
Questions about Ab Testing
What does Ab Testing do?
When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Ab Testing is an agent skill from Cesarjoquin/Marketing-Skills. When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program.
When should I use Ab Testing?
Ab Testing fits situations like: implement an A/B test; build a growth experimentation program; the user mentions A/B test; test this change.
How do I install Ab Testing in Claude Code?
Run `npx skills add Cesarjoquin/Marketing-Skills --skill ab-testing -a claude-code`. Or copy the skill folder (skills/ab-testing in Cesarjoquin/Marketing-Skills) into .claude/skills/ab-testing in your project. Claude Code loads it when a task matches its description.
How do I install Ab Testing in Codex?
Run `npx skills add Cesarjoquin/Marketing-Skills --skill ab-testing -a codex`. Or copy the skill folder (skills/ab-testing in Cesarjoquin/Marketing-Skills) into .agents/skills/ab-testing in your project. Codex loads it when a task matches its description.
Can I use Ab Testing 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 Cesarjoquin/Marketing-Skills --skill ab-testing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ab-testing, .gemini/skills/ab-testing, .github/skills/ab-testing and .opencode/skills/ab-testing in your project.
What does Ab Testing need to run?
SKILL.md names no scripts, command-line tools or credentials: Ab Testing is instructions for the agent only.
Does Ab Testing access the network?
SKILL.md names 2 domains. As links in the text: evanmiller.org and optimizely.com. This is read from the text; nothing was executed.
Is Ab Testing 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 Ab Testing use?
Ab Testing is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Ab Testing use?
About 2.8k tokens (SKILL.md is roughly 11k 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 3.5k tokens, read only when the agent opens those files.
What are the alternatives to Ab Testing?
Skills that share tags, products or a category with Ab Testing: Analytics (Nexus-JPF/note-companion, 869 stars), Ab Test Setup (freekmurze/dotfiles, 1k stars), Ad Test Designer (aaron-he-zhu/aaron-marketing-skills, 2.9k stars) and Meta Tags Optimizer (nowork-studio/notfair-plugin, 3.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Ab Testing?
Cesarjoquin (a GitHub user) maintains it in Cesarjoquin/Marketing-Skills, which has 199 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on September 14, 2026.
Source: Cesarjoquin/Marketing-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.