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 leonardodalinky/SciDER --skill statistical-analysisgit clone --depth 1 https://github.com/leonardodalinky/SciDERWrote 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/leonardodalinky/scider/statistical-analysis)<a href="https://agentmods.dev/skills/leonardodalinky/scider/statistical-analysis"><img src="https://agentmods.dev/badge/skills/leonardodalinky/scider/statistical-analysis/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/leonardodalinky/scider/statistical-analysis"><img src="https://agentmods.dev/badge/skills/leonardodalinky/scider/statistical-analysis.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 | $0.00036 | $0.05103 |
| Opus 5.5 | $0.00014 | $0.02041 |
| Sonnet 5.5 | $0.00007 | $0.01021 |
| Haiku 4.5 | $0.00004 | $0.00510 |
Grade A, and why
statistical-analysis 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.
This is a copy
94% identical to statistical-analysis — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 628 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Statistical Analysis
Overview
Statistical analysis is a systematic process for testing hypotheses and quantifying relationships. Conduct hypothesis tests (t-test, ANOVA, chi-square), regression, correlation, and Bayesian analyses with assumption checks and APA reporting. Apply this skill for academic research.
When to Use This Skill
This skill should be used when:
- Conducting statistical hypothesis tests (t-tests, ANOVA, chi-square)
- Performing regression or correlation analyses
- Running Bayesian statistical analyses
- Checking statistical assumptions and diagnostics
- Calculating effect sizes and conducting power analyses
- Reporting statistical results in APA format
- Analyzing experimental or observational data for research
Core Capabilities
1. Test Selection and Planning
- Choose appropriate statistical tests based on research questions and data characteristics
- Conduct a priori power analyses to determine required sample sizes
- Plan analysis strategies including multiple comparison corrections
2. Assumption Checking
- Automatically verify all relevant assumptions before running tests
- Provide diagnostic visualizations (Q-Q plots, residual plots, box plots)
- Recommend remedial actions when assumptions are violated
3. Statistical Testing
- Hypothesis testing: t-tests, ANOVA, chi-square, non-parametric alternatives
- Regression: linear, multiple, logistic, with diagnostics
- Correlations: Pearson, Spearman, with confidence intervals
- Bayesian alternatives: Bayesian t-tests, ANOVA, regression with Bayes Factors
4. Effect Sizes and Interpretation
- Calculate and interpret appropriate effect sizes for all analyses
- Provide confidence intervals for effect estimates
- Distinguish statistical from practical significance
5. Professional Reporting
- Generate APA-style statistical reports
- Create publication-ready figures and tables
- Provide complete interpretation with all required statistics
Workflow Decision Tree
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.
- 1mo ago First seen · 628 lines · 36 tokens per session scan A 685db09572d1
statistical-analysis is a skill published in the GitHub repository leonardodalinky/SciDER (88 stars, last pushed 13d ago), licensed Apache-2.0. It adds 36 tokens to every session and 5,103 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to statistical-analysis, differing in 7 lines, and is treated as a copy.
Other skills, from other repositories
paper-writer
Drafts publishable paper prose from the author's own materials, from a single paragraph to a full manuscript, across STEM and non-STEM fields. Every factual claim traces to user input, verified retrieval, or field common knowledge; citations pass an independent verification ladder; delivery is clean prose with zero…
intro-drafter
Drafts the Introduction prose for a technical paper, guided internally by a six-paragraph flowchart: background and running example, existing limitations, problem essence and goal, key challenges, solution overview, contributions. Positions the paper as Technique or New Problem/Setting, aligns contributions with…
paper-polish
Polishes existing academic prose while preserving the author's meaning: grammar and flow repair, tone calibration against evidence strength, AI-tone removal, and Chinese-to-English rewriting at submission quality. Never fabricates data, citations, or claims, and flags any edit that could change scientific meaning. Use…
pre-submission-reviewer
Runs a pre-submission review of a technical paper across five dimensions: macro logic, writing details, English grammar, LaTeX formatting, and figure quality. Uses a reviewer-style severity taxonomy (CRITICAL / MAJOR / MINOR) and flags banned AI-tone vocabulary and em-dash misuse. Use when the user asks to 'review…
figure-designer
Advises on the design of the three core figures in a technical paper: the Motivated Example (Figure 1), the Solution Overview (Methodology), and the Experimental Results figures. Recommends the right design paradigm, layout, labelling, and tool for each figure type, then runs a quality-control audit. Use when the user…
0-osp-onboarding
OSP Phase 0: Venue lookup, paper detection, criteria scaffolding.