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 ai-analyst-lab/ai-analyst --skill experiment-briefgit clone --depth 1 https://github.com/ai-analyst-lab/ai-analystWrote 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/ai-analyst-lab/ai-analyst/experiment-brief)<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst/experiment-brief"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/experiment-brief/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/ai-analyst-lab/ai-analyst/experiment-brief"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/experiment-brief.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 | $0.00275 | $0.02759 |
| Opus 5 | $0.00138 | $0.01380 |
| Sonnet 5 | $0.00055 | $0.00552 |
| Haiku 4.5 | $0.00028 | $0.00276 |
Grade A, and why
experiment-brief 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 2d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- experiment-brief — 86% identical, 19 lines differ
How it starts
The opening of the file, as written. The whole thing — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Experiment Brief
Purpose
Auto-generate a structured experiment brief when a user expresses intent to test something. This is the "think before you design" safety net — ensuring every experiment starts with a clear hypothesis, north star metric, guardrail metrics, success criteria, and duration estimate before the Experiment Designer agent runs.
When to Use
Apply this skill when:
- The user says "I want to test..." or "Let's experiment with..." or "Should we A/B test..." or any variant expressing intent to run an experiment
- Before invoking the Experiment Designer agent — the brief is a prerequisite input
- When an experiment request is vague — the user wants to test something but hasn't specified metrics, duration, or success criteria
This skill auto-fires on experiment intent detection. Do NOT wait to be asked.
Critical Requirements
The brief must be COMPLETE and ACTIONABLE:
- No "TBD" placeholders — all decisions are made in the brief
- No "Would you like me to..." deferral — do the work now
- No missing thresholds — every guardrail has a number
- No ambiguous success criteria — ship/kill/iterate conditions are specific
- Always includes a VIABLE/MARGINAL/NOT_VIABLE feasibility flag
If the user provides baseline values, VALIDATE them by querying the data first. Correct misstatements with actual numbers before using them in the brief.
Instructions
What Is an Experiment Brief?
An experiment brief is a one-page document that captures the essential decisions BEFORE any statistical design work begins. It answers: What are we testing? Why? How will we know if it worked? What must we not break?
EXPERIMENT BRIEF
━━━━━━━━━━━━━━━━
WHAT: What change are we testing?
WHY: What business outcome do we expect?
HYPOTHESIS: We believe [change] will [impact metric] because [reason]
NORTH STAR: The ONE metric we're trying to move
GUARDRAILS: Metrics that must NOT degrade
SUCCESS: What result would make us ship?
DURATION: Rough estimate of how long we'd need to run
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.
- 2d ago First seen · 203 lines · 275 tokens per session scan A e47dc34ea1bb
experiment-brief is a skill published in the GitHub repository ai-analyst-lab/ai-analyst (298 stars, last pushed 3d ago), licensed MIT. It adds 275 tokens to every session and 2,759 once invoked, about $0.0014 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 2026-09-12.
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