Agent skill

Smr Empirical Illustration

by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills

A skill your agent uses when building the real-data empirical illustration for a Sociological Methods & Research (SMR) paper — a demonstration that the method changes a substantive conclusion, not a…

MITAuto-check passed

Install Smr Empirical Illustration

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill smr-empirical-illustration -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills smr-empirical-illustration --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Sociological-Methods-and-Research-Skills/skills/smr-empirical-illustration .claude/skills/smr-empirical-illustration && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
smr-empirical-illustration
GitHub stars
1.2k
Token cost
~1.1k tokens
SKILL.md length
539 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when building the real-data empirical illustration for a Sociological Methods & Research (SMR) paper — a demonstration that the method changes a substantive conclusion, not a…

  • Not a decorative example
  • SKILL.md covers The "it changes the answer"…, Choosing the dataset, What to report and Keep it an illustration, not a…, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Smr Empirical Illustration is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when building the real-data empirical illustration for a Sociological Methods & Research (SMR) paper — a demonstration that the method changes a substantive conclusion, not a decorative example. Designs the illustration; does not derive properties or design the Monte Carlo.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. | 覆盖主流期刊的… The licence is MIT.

When your agent uses it

  • Not a decorative example

Example prompts

  • “/smr-empirical-illustration”

What it can do on your machine

Read from SKILL.md and the folder at commit 932eb23. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Smr Empirical Illustration loads about 1.1k tokens when it runs. Until then it costs about 76 tokens; SKILL.md has 539 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~76
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 539 words, ~1,098 tokens.

Download SKILL.mdSave it as .claude/skills/smr-empirical-illustration/SKILL.md (or your agent's skills folder).
name
smr-empirical-illustration
description
Use when building the real-data empirical illustration for a Sociological Methods & Research (SMR) paper — a demonstration that the method changes a substantive conclusion, not a decorative example. Designs the illustration; does not derive properties or design the Monte Carlo.

SMR Empirical Illustration

Use this to make the real-data section earn its place. SMR expects a methods paper to show that the method matters substantively — that using it instead of the incumbent leads to a different, better-justified conclusion about the social world. A throwaway "we also applied it to some data" section is a reviewer flag.

The "it changes the answer" standard

The illustration's job is to demonstrate consequence:

  • Run the incumbent and the new method on the same data, and show where they diverge. The payoff sentence is "the standard approach would have concluded X; our method shows Y, and Y is the defensible answer because [reason tied to the method's properties]."
  • Tie the divergence to the mechanism established in smr-derivation-and-properties and the regime identified in smr-simulation-studies: the data should sit in the regime where the incumbent is known to fail.
  • State the substantive stake: who would have made a wrong inference, and about what, if they had used the old method? The stake makes the method consequential, not just correct.

Choosing the dataset

  • Pick data that lives in the failure regime (e.g., few clusters, non-invariance across groups, informative missingness, network dependence) so the method has something to do.
  • Prefer public or depositable data — SMR's availability policy expects the data and code behind the illustration to be accessible (see smr-software-and-reproducibility). If data are restricted, plan the availability statement now.
  • A familiar, recognizable dataset lets readers judge the result against intuition; an exotic one forces them to trust you on both the data and the method.

What to report

ElementPurpose
Side-by-side incumbent vs. new methodShow the divergence concretely
The substantive conclusion under eachMake the stake visible
A diagnostic that the data are in the failure regimeJustify why the new method is needed here
Uncertainty for both methodsAvoid replacing one overconfident answer with another
Link to released code/dataSatisfy reproducibility expectations
Show full SKILL.md (224 more words)Show less

Keep it an illustration, not a substantive paper

The danger runs both ways. Too thin and it is decorative; too thick and the paper becomes a substantive study that belongs in ASR/AJS (the failure flagged in smr-topic-selection). Calibrate: the illustration should be deep enough to show the method changes the answer, and no deeper. The unit of analysis is the method's behavior on real data, not a full substantive argument with its own literature.

Checklist

  • Incumbent and new method are run on the same data with results side by side.
  • The divergence is tied to the method's mechanism and the simulated failure regime.
  • The substantive stake (who would be wrong, about what) is stated.
  • A diagnostic shows the data are actually in the regime where the method is needed.
  • Uncertainty is reported for both methods.
  • Data are public/depositable, or a restricted-data availability plan exists.
  • The section stays an illustration, not a full substantive study.

Anti-patterns

  • Decorative application: the method is run, but it would not change any conclusion.
  • Regime mismatch: data where the incumbent is fine, so the new method has nothing to prove.
  • Substantive creep: the illustration grows into an ASR/AJS-style paper and loses methods focus.
  • One-method reporting: showing only the new method's result, hiding what the incumbent would say.
  • Inaccessible data with no plan: an illustration readers can never reproduce.

Output format

text
[Illustration status] consequential / decorative / not ready
[Dataset + regime] <data : why it sits in the failure regime>
[Divergence] <incumbent conclusion vs. new-method conclusion>
[Substantive stake] <who would have been wrong, about what>
[Reproducibility] data/code accessible? restricted-data plan?
[Next SMR skill] smr-tables-figures

© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in Sociological-Methods-and-Research-Skills/skills/smr-empirical-illustration of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

Compare with similar skills

Smr Empirical Illustration next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Smr Empirical Illustration compared with similar skills
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Smr Empirical Illustration this skillbrycewang-stanford/Awesome-Journal-Skills1.2k—~1.1kAutomated safety check: PassMIT
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Santa Methodaffaan-m/ECC276k—~2.1kAutomated safety check: PassMIT
Santa Methodaffaan-m/ECC276k—~1.9kAutomated safety check: PassMIT
Article Illustrationssickn33/agentic-awesome-skills47k1 repos~1.6kAutomated safety check: PassMIT
Sociology Research Methodswentorai/research-plugins2981 repos~1.9kAutomated safety check: PassMIT

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Questions about Smr Empirical Illustration

What does Smr Empirical Illustration do?

A skill your agent uses when building the real-data empirical illustration for a Sociological Methods & Research (SMR) paper — a demonstration that the method changes a substantive conclusion, not a…. Smr Empirical Illustration is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when building the real-data empirical illustration for a Sociological Methods & Research (SMR) paper — a demonstration that the method changes a substantive conclusion, not a decorative example.

When should I use Smr Empirical Illustration?

Smr Empirical Illustration fits situations like: not a decorative example.

How do I install Smr Empirical Illustration in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill smr-empirical-illustration -a claude-code`. Or copy the skill folder (Sociological-Methods-and-Research-Skills/skills/smr-empirical-illustration in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/smr-empirical-illustration in your project. Claude Code loads it when a task matches its description.

How do I install Smr Empirical Illustration in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill smr-empirical-illustration -a codex`. Or copy the skill folder (Sociological-Methods-and-Research-Skills/skills/smr-empirical-illustration in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/smr-empirical-illustration in your project. Codex loads it when a task matches its description.

Can I use Smr Empirical Illustration in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill smr-empirical-illustration -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/smr-empirical-illustration, .gemini/skills/smr-empirical-illustration, .github/skills/smr-empirical-illustration and .opencode/skills/smr-empirical-illustration in your project.

What does Smr Empirical Illustration need to run?

SKILL.md names no scripts, command-line tools or credentials: Smr Empirical Illustration is instructions for the agent only.

Does Smr Empirical Illustration access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Smr Empirical Illustration safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Smr Empirical Illustration use?

Smr Empirical Illustration is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Smr Empirical Illustration use?

About 1.1k tokens (SKILL.md is roughly 4.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Smr Empirical Illustration?

Skills that share tags, products or a category with Smr Empirical Illustration: Santa Method (affaan-m/ECC, 277k stars), Santa Method (affaan-m/ECC, 276k stars), Santa Method (affaan-m/ECC, 276k stars) and Article Illustrations (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Smr Empirical Illustration?

brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,231 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.

Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.