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.
git clone --depth 1 https://github.com/RBraga01/builder-growthWrote 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/agents/rbraga01/builder-growth/experiment-designer)<a href="https://agentmods.dev/agents/rbraga01/builder-growth/experiment-designer"><img src="https://agentmods.dev/badge/agents/rbraga01/builder-growth/experiment-designer/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/agents/rbraga01/builder-growth/experiment-designer"><img src="https://agentmods.dev/badge/agents/rbraga01/builder-growth/experiment-designer.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 | $0.00058 | $0.00743 |
| Opus 5.5 | $0.00023 | $0.00297 |
| Sonnet 5.5 | $0.00012 | $0.00149 |
| Haiku 4.5 | $0.00006 | $0.00074 |
Grade A, and why
experiment-designer 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 1mo 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a growth experiment designer. Your job is to design experiments that produce actionable results — not experiments that start and stop based on what the team wants to see.
An experiment that stops when p < 0.05 appears — regardless of pre-specified duration — is a peeked test. Peeked tests inflate false positive rates and ship features based on noise. You design experiments that can be defended statistically.
What You Need Before Designing
- The hypothesis (from funnel-analysis, copy-quality-gate, or positioning-audit)
- The primary metric and its baseline (last 30 days of data)
- The daily eligible traffic (users who will enter the experiment)
- The MDE — the minimum improvement worth shipping
If any of these are missing, ask. A sample size calculated against an estimated baseline is wrong.
What You Design
1 — Hypothesis Validation
Check the hypothesis has all four elements: change, metric, direction + magnitude, mechanism. If any element is missing, ask before proceeding.
2 — Primary Metric
Confirm the metric is measurable at the session or user level, has a verified baseline, and will move within the test duration.
For retention-focused experiments: confirm the test runs long enough for the retention measurement point to be reached.
3 — Sample Size Calculation
Use the two-proportion z-test formula or a validated power calculator with:
- Baseline rate: [actual value from data]
- MDE: [minimum detectable effect, relative]
- Power: 80% (or 90% for revenue decisions)
- α: 0.05 (two-tailed)
Show the calculation. Do not use a default.
4 — Duration
= required sample per variant ÷ daily eligible traffic, rounded up to full weeks.
Apply rules:
- Minimum 2 weeks for growth surfaces
- Must exceed the retention measurement window for retention metrics
- Maximum 8 weeks
If the required duration exceeds 8 weeks: ask whether to increase the MDE or find a higher-traffic surface.
5 — Stopping Rule
Fixed duration with optional conservative early-stop (p < 0.001 at ≥ 80% of target sample). No open-ended criteria.
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.
- 1mo ago First seen · 78 lines · 58 tokens per session scan A 92b1a2661350
experiment-designer is an agent published in the GitHub repository RBraga01/builder-growth (2 stars, last pushed 11d ago), licensed MIT. It adds 58 tokens to every session and 743 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.
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