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Paid Media Experiment Designer

Designs and reads out A/B tests for paid ads, with sample size, duration and decision rules

Source Download skill
Repository
AgriciDaniel/claude-ads
Stars
10,667
Licence
MIT
Files
1 file

What it does

Once installed, the agent plans paid-advertising tests more rigorously. Before running anything, it works through the decision being made, the hypothesis, the control and treatment groups, the main success metric, safety metrics that must not get worse, and when to stop. It estimates how many people and how many days a test needs, and it reads results only after checking that the data is complete and that groups were assigned properly. It returns the setup or results as structured JSON with a plain-language recommendation, and it warns against stopping early on a lucky result or calling a small, noisy difference a win.

Great for

  • Marketers running A/B or split tests on ad campaigns who want a sound test plan before spending budget
  • Analysts who need sample-size and test-duration estimates for paid media experiments
  • Teams reviewing whether an ad experiment's results are statistically trustworthy before acting on them

Skip it if

  • Simple campaign setup or copywriting with no need for experimental design, where the skill adds unnecessary process
  • Making final business decisions on its own: its statistics depend on assumptions you supply, and the skill itself does not check real platform data or verify results
  • Situations needing a formal statistical audit: the skill gives guidance and approximations, which should be reviewed by someone qualified before high-stakes spending decisions

Try asking

  • “Design an A/B test for two headlines on our Google Ads campaign, including sample size and how long to run it”
  • “Here is the readout from our Meta split test; check assignment integrity and tell me whether the result is real”
  • “What minimum detectable effect and duration should we assume for a landing-page test with about 2,000 clicks a week?”
  • “Help me write a pre-registered analysis plan and stopping rule for a paid search bidding experiment”
Step-by-step guide: how to use Paid Media Experiment DesignerInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 1 original files, the MIT licence and an attribution note.

    ads-test.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip ads-test.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip ads-test.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Provide your assumptions up front: baseline conversion rate, the smallest effect worth detecting, weekly traffic and conversion lag, so the sample-size estimate is meaningful
  • Share the raw exported data or the platform's experiment report when asking for a readout, rather than only a summary
  • Treat the output as a planning aid; check the statistics against your platform's own experiment tools before committing budget

What's inside

  • SKILL.md

Redistributed unmodified from AgriciDaniel/claude-ads under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.