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 flonat/flonat-research --skill experiment-designgit clone --depth 1 https://github.com/flonat/flonat-researchWrote 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/flonat/flonat-research/experiment-design)<a href="https://agentmods.dev/skills/flonat/flonat-research/experiment-design"><img src="https://agentmods.dev/badge/skills/flonat/flonat-research/experiment-design/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/flonat/flonat-research/experiment-design"><img src="https://agentmods.dev/badge/skills/flonat/flonat-research/experiment-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00049 | $0.02135 |
| Opus 5 | $0.00024 | $0.01068 |
| Sonnet 5 | $0.00010 | $0.00427 |
| Haiku 4.5 | $0.00005 | $0.00214 |
Grade A, and why
experiment-design 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 5d 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 — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Experiment Design
Interview-driven design workflow producing design documents, power analysis scripts, and pre-analysis plans.
Modes
| Mode | What it produces | Entry point |
|---|---|---|
| Power | Power analysis script + sample size table | "How many participants do I need?" |
| Design | Full design document (hypotheses, conditions, measures, randomization) | "Design my experiment" |
| PAP | Pre-analysis plan (AEA/OSF/EGAP format) | "Write a PAP" |
| Survey | Structured survey specification from natural language or QSF | "Build a survey" / "Parse my Qualtrics" |
Default: Design. If user provides a .qsf file, auto-select Survey mode.
When to Use
- Designing a new experiment or survey
- Calculating required sample sizes
- Writing or auditing a pre-analysis plan
- Parsing a Qualtrics
.qsffile to understand its structure - Building a survey specification from a natural language description
When NOT to Use
- Running the analysis →
data-analysis - Auditing identification strategy for observational studies →
causal-design - Generating synthetic test data →
synthetic-data
Shared References
- Method probing questions:
shared/method-probing-questions.md— ask before designing (Experiments/RCTs, Survey sections) - Validation tiers:
shared/validation-tiers.md— tier determines required power and pre-registration - Escalation protocol:
shared/escalation-protocol.md— escalate when design has validity threats - Engagement-stratified sampling:
shared/engagement-stratified-sampling.md— stratify social media samples by engagement - Inter-coder reliability:
shared/intercoder-reliability.md— reliability planning for content analysis designs
Mode: Power
Read references/power-analysis-recipes.md for language-specific code patterns.
Workflow
- Interview — ask for:
- Primary outcome variable and expected effect size (or domain norms)
- Design type (between-subjects, within-subjects, factorial, cluster-randomized)
- Number of conditions/groups
- Significance level (default: 0.05) and desired power (default: 0.80)
- Any clustering or stratification
- Generate script — R (
DeclareDesign/pwr) or Python (statsmodels.stats.power) - Execute and report — produce a sample size table showing N for power = {0.80, 0.90, 0.95}
- Write to project — save script to
code/power_analysis.R(or.py), results tooutput/power_analysis_results.md
What ships with it
6 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.
- 5d ago First seen · 189 lines · 49 tokens per session scan A 6bf98b379951
experiment-design is a skill published in the GitHub repository flonat/flonat-research (132 stars, last pushed 14d ago), licensed MIT. It adds 49 tokens to every session and 2,135 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 2026-09-03.
Other skills, from other repositories
latex-compile
Compile a LaTeX document and fix every error plus aesthetic issue (overfull/underfull boxes, widows, alignment, fonts) for a clean PDF and log. Use this instead of running pdflatex/latexmk manually — it avoids the latexmk stale-log trap and silent grep failures on binary log output, and it reformats rather than…
nb-to-wolfbook
Convert Mathematica .nb or .m files to Wolfbook .wb format so they open and run in VS Code. Use when bringing existing .nb/.m files into Wolfbook, or to make an existing .wb bridge-safe.
sync-wb-nb
Propagate a change made in a Wolfbook .wb notebook into the paired .nb notebook so the two stay identical. Use immediately after every .wb edit.
wolfram-headless
Run heavy Wolfram Language (wolframscript) computations from Claude Code reliably, and diagnose the misleading "The product exited because of a license error". Use whenever invoking wolframscript on a non-trivial computation, when a wolframscript job dies with a "license error" despite a valid license, or when Wolfram…
cross-validate
Format a result, derivation, or numerical value for independent verification by a second model. Use when you want a cross-check on an important or contested result.
verify-citation
Confirm a paper actually exists (arXiv / Semantic Scholar / OpenAlex) before citing it. Use before writing any new citation.