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 wentorai/research-plugins --skill stata-analyst-guidegit clone --depth 1 https://github.com/wentorai/research-pluginsWrote 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/wentorai/research-plugins/stata-analyst-guide)<a href="https://agentmods.dev/skills/wentorai/research-plugins/stata-analyst-guide"><img src="https://agentmods.dev/badge/skills/wentorai/research-plugins/stata-analyst-guide.svg" alt="Measured on agentmods" 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 | $0.00017 | $0.01923 |
| Opus 5 | $0.00009 | $0.00962 |
| Sonnet 5 | $0.00003 | $0.00385 |
| Haiku 4.5 | $0.00002 | $0.00192 |
Grade A, and why
stata-analyst-guide 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.
How it starts
The opening of the file, as written. The whole thing — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Stata Analyst Guide for Social Science Research
Complete Stata workflow for sociology and social science research, from survey data preparation through publication-ready regression tables and visualizations. This skill covers the analytical techniques most commonly used in top sociology journals.
Overview
Stata is the dominant statistical software in sociology, political science, demography, and many social science disciplines. Its command-line interface, reproducible do-file workflow, and comprehensive support for survey data, multilevel models, and categorical data analysis make it the tool of choice for researchers working with complex social datasets.
This skill provides ready-to-use Stata code for the most common analytical tasks in social science research: descriptive statistics for diverse variable types, regression modeling with proper controls and robustness checks, interaction effects with meaningful visualizations, and automated production of APA/ASA-formatted tables suitable for direct inclusion in journal manuscripts.
The examples draw on typical social science data structures: individual-level survey data with sampling weights, nested data (individuals within organizations or regions), longitudinal panels, and event-history data. All code follows the conventions expected by reviewers at journals such as the American Sociological Review, American Journal of Sociology, and Social Forces.
Descriptive Statistics
Weighted Summary Statistics
* Social science surveys typically require survey weights
svyset psu [pweight=finalweight], strata(stratum)
* Weighted means and proportions
svy: mean income education_years age
svy: proportion race gender marital_status
* Weighted cross-tabulation
svy: tabulate education_cat income_quintile, row se
* Descriptive statistics table for paper
estpost summarize age education_years income ///
children household_size, detail
esttab using "tables/descriptives.tex", ///
cells("mean(fmt(2)) sd(fmt(2)) min max count") ///
label title("Descriptive Statistics") replace
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 · 246 lines · 17 tokens per session scan A 41165022f6ab
stata-analyst-guide is a skill published in the GitHub repository wentorai/research-plugins (288 stars, last pushed 2mo ago), licensed MIT. It adds 17 tokens to every session and 1,923 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…
exploratory-data-analysis
Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…
matlab
Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
phylogenetics
Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
mapping-to-snomed
Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…