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 cnfeat/top-pm-skills --skill ab-test-plannergit clone --depth 1 https://github.com/cnfeat/top-pm-skillsWrote 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/cnfeat/top-pm-skills/ab-test-planner)<a href="https://agentmods.dev/skills/cnfeat/top-pm-skills/ab-test-planner"><img src="https://agentmods.dev/badge/skills/cnfeat/top-pm-skills/ab-test-planner/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/cnfeat/top-pm-skills/ab-test-planner"><img src="https://agentmods.dev/badge/skills/cnfeat/top-pm-skills/ab-test-planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00077 | $0.01273 |
| Opus 5 | $0.00039 | $0.00636 |
| Sonnet 5 | $0.00015 | $0.00255 |
| Haiku 4.5 | $0.00008 | $0.00127 |
Grade A, and why
ab-test-planner 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 8d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
A/B Test Planner Skill
Design experiments that produce trustworthy results — not just directional signals. Every test output includes hypothesis, success metrics, sample size, duration, and a results interpretation guide.
Required Inputs
Ask the user for these if not provided:
- What is being tested (feature, UI change, copy, pricing, onboarding step)
- Hypothesis (or ask to help formulate one)
- Primary metric (conversion rate, click-through, completion rate, etc.)
- Baseline rate and minimum detectable effect (MDE)
- Daily eligible users (to calculate duration)
Experiment Design Checklist
Before running any test, confirm:
- Clear hypothesis with predicted direction
- Single primary metric (plus up to 2 guardrail metrics)
- Minimum detectable effect (MDE) defined
- Sample size calculated
- Test duration estimated
- Segment isolated (no overlap with other running tests)
- Rollback plan defined
Hypothesis Template
"We believe that [change] will cause [primary metric] to [increase/decrease] by [X%] for [user segment], because [rationale based on data or insight]."
Never run a test without a directional hypothesis. "Let's just see what happens" is not a hypothesis.
Sample Size Calculator Logic
Use this formula (provide the output, not the formula, to the user):
- Baseline conversion rate: Current rate of primary metric
- MDE: Smallest change worth detecting (recommend 10–20% relative lift for most features)
- Statistical power: 80% (standard)
- Significance level: 95% (p < 0.05)
For common scenarios, provide pre-calculated estimates:
| Baseline Rate | MDE (Relative) | Required Sample per Variant |
|---|---|---|
| 5% | 20% | ~19,000 |
| 10% | 15% | ~14,000 |
| 20% | 10% | ~15,000 |
| 40% | 10% | ~9,500 |
| 60% | 5% | ~42,000 |
Always warn: "These are estimates. Use a tool like Evan Miller's calculator or Statsig for precision."
Test Duration Guidance
Minimum: 2 full weeks (to capture weekly seasonality) Maximum: 4 weeks (novelty effect distorts results beyond this)
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.
- 8d ago First seen · 122 lines · 77 tokens per session scan A 96f8254c308c
ab-test-planner is a skill published in the GitHub repository cnfeat/top-pm-skills (48 stars, last pushed 3mo ago), licensed MIT. It adds 77 tokens to every session and 1,273 once invoked, about $0.0004 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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