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 guia-matthieu/clawfu-skills --skill ab-test-statsgit clone --depth 1 https://github.com/guia-matthieu/clawfu-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/guia-matthieu/clawfu-skills/ab-test-stats)<a href="https://agentmods.dev/skills/guia-matthieu/clawfu-skills/ab-test-stats"><img src="https://agentmods.dev/badge/skills/guia-matthieu/clawfu-skills/ab-test-stats/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/guia-matthieu/clawfu-skills/ab-test-stats"><img src="https://agentmods.dev/badge/skills/guia-matthieu/clawfu-skills/ab-test-stats.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 | $0.00039 | $0.01036 |
| Opus 5 | $0.00019 | $0.00518 |
| Sonnet 5 | $0.00008 | $0.00207 |
| Haiku 4.5 | $0.00004 | $0.00104 |
Grade A, and why
ab-test-stats 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 11d 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
A/B Test Statistics Calculator
Calculate statistical significance for A/B tests - know when your results are real, not random chance.
When to Use This Skill
- Test analysis - Determine if results are statistically significant
- Sample planning - Calculate required sample size before testing
- Duration estimation - Know how long to run experiments
- Power analysis - Ensure tests can detect meaningful differences
What Claude Does vs What You Decide
| Claude Does | You Decide |
|---|---|
| Structures analysis frameworks | Metric definitions |
| Identifies patterns in data | Business interpretation |
| Creates visualization templates | Dashboard design |
| Suggests optimization areas | Action priorities |
| Calculates statistical measures | Decision thresholds |
Dependencies
pip install scipy numpy click
Commands
Check Significance
python scripts/main.py significance --control 1000,50 --variant 1000,65
python scripts/main.py significance --control 5000,250 --variant 5000,300 --confidence 0.99
Calculate Sample Size
python scripts/main.py sample-size --baseline 0.05 --mde 0.02
python scripts/main.py sample-size --baseline 0.10 --mde 0.01 --power 0.90
Estimate Duration
python scripts/main.py duration --traffic 1000 --baseline 0.05 --mde 0.02
Examples
Example 1: Analyze Test Results
# Control: 1000 visitors, 50 conversions (5%)
# Variant: 1000 visitors, 65 conversions (6.5%)
python scripts/main.py significance --control 1000,50 --variant 1000,65
# Output:
# A/B Test Results
# ─────────────────────────
# Control: 5.00% (50/1000)
# Variant: 6.50% (65/1000)
# Lift: +30.0%
#
# Statistical Analysis
# ─────────────────────────
# p-value: 0.089
# Confidence: 91.1%
# Result: NOT SIGNIFICANT (need 95%)
#
# Recommendation: Continue test for more data
Example 2: Plan Sample Size
# Baseline 5% conversion, want to detect 20% relative lift (1% absolute)
python scripts/main.py sample-size --baseline 0.05 --mde 0.01
# Output:
# Sample Size Calculator
# ──────────────────────────────
# Baseline conversion: 5.0%
# Minimum detectable effect: 1.0% (20% relative)
# Target conversion: 6.0%
#
# Required per variant: 3,842 visitors
# Total required: 7,684 visitors
#
# At 1000 daily visitors: ~8 days
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 149 lines · 39 tokens per session scan A e5ff71348607
ab-test-stats is a skill published in the GitHub repository guia-matthieu/clawfu-skills (149 stars, last pushed 5mo ago), licensed MIT. It adds 39 tokens to every session and 1,036 once invoked, about $0.0002 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 2026-08-30.
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