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 jeremylongworth-source/AgentSkills --skill experiment-design-validationgit clone --depth 1 https://github.com/jeremylongworth-source/AgentSkillsWrote 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/jeremylongworth-source/agentskills/experiment-design-validation)<a href="https://agentmods.dev/skills/jeremylongworth-source/agentskills/experiment-design-validation"><img src="https://agentmods.dev/badge/skills/jeremylongworth-source/agentskills/experiment-design-validation/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/jeremylongworth-source/agentskills/experiment-design-validation"><img src="https://agentmods.dev/badge/skills/jeremylongworth-source/agentskills/experiment-design-validation.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 | $0.00071 | $0.00341 |
| Opus 5 | $0.00036 | $0.00170 |
| Sonnet 5 | $0.00014 | $0.00068 |
| Haiku 4.5 | $0.00007 | $0.00034 |
Grade A, and why
experiment-design-validation 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 7d 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.
What it actually says
Experiment Design Validation
Core Workflow
- Define the decision the experiment will inform.
- Write a falsifiable hypothesis with target audience, change, expected behavior, and reason.
- Choose method: A/B test, holdout, fake-door test, concierge test, prototype test, usability test, smoke test, survey, landing-page test, or qualitative validation.
- Define primary metric, guardrail metrics, segmentation, exposure rules, sample/traffic constraints, duration, and stop criteria.
- Plan instrumentation and QA before launch.
- Decide in advance how results will be interpreted and what action follows.
- Record result, learning, caveats, and next experiment.
Freshness Rule
Verify current analytics, experimentation platform, privacy, consent, and ad-platform docs before giving tactical setup guidance for A/B tools, GA4/Firebase events, conversion tracking, targeting, or experiment allocation.
Deliverable Shape
For experiment work, provide:
- Decision and hypothesis
- Target audience and eligibility
- Variant/control design
- Primary and guardrail metrics
- Instrumentation and QA plan
- Duration/sample considerations
- Decision rules and follow-up actions
References
- Read
references/experiment-design-checklist.mdwhen designing or reviewing an experiment.
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.
- 7d ago First seen · 38 lines · 71 tokens per session scan A 29af0a90e428
experiment-design-validation is a skill published in the GitHub repository jeremylongworth-source/AgentSkills (1 stars, last pushed 8d ago), licensed MIT. It adds 71 tokens to every session and 341 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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build-test
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