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A skill your agent uses when deciding how much theory or structure a The Review of Economics and Statistics (REStat) manuscript should carry — right-sizing a model so it interprets or disciplines…
Install Restat Theory Model
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill restat-theory-model -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills restat-theory-model --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Review-of-Economics-and-Statistics-Skills/skills/restat-theory-model .claude/skills/restat-theory-model && rm -rf skills-srcUse ~/.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/
Install the "restat-theory-model" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Review-of-Economics-and-Statistics-Skills/skills/restat-theory-model into .claude/skills/restat-theory-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "restat-theory-model", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Review-of-Economics-and-Statistics-Skills/skills/restat-theory-modelType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill restat-theory-model -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills restat-theory-model --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/Review-of-Economics-and-Statistics-Skills/skills/restat-theory-model .agents/skills/restat-theory-model && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "restat-theory-model" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Review-of-Economics-and-Statistics-Skills/skills/restat-theory-model into .agents/skills/restat-theory-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "restat-theory-model", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill restat-theory-model -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills restat-theory-model --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/Review-of-Economics-and-Statistics-Skills/skills/restat-theory-model .cursor/skills/restat-theory-model && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "restat-theory-model" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Review-of-Economics-and-Statistics-Skills/skills/restat-theory-model into .cursor/skills/restat-theory-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "restat-theory-model", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/brycewang-stanford/Awesome-Journal-Skills.git --path Review-of-Economics-and-Statistics-Skills/skills/restat-theory-model--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill restat-theory-model -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills restat-theory-model --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/Review-of-Economics-and-Statistics-Skills/skills/restat-theory-model .gemini/skills/restat-theory-model && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "restat-theory-model" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Review-of-Economics-and-Statistics-Skills/skills/restat-theory-model into .gemini/skills/restat-theory-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "restat-theory-model", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills restat-theory-modelInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill restat-theory-model -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/Review-of-Economics-and-Statistics-Skills/skills/restat-theory-model .github/skills/restat-theory-model && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "restat-theory-model" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Review-of-Economics-and-Statistics-Skills/skills/restat-theory-model into .github/skills/restat-theory-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "restat-theory-model", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill restat-theory-model -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills restat-theory-model --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/Review-of-Economics-and-Statistics-Skills/skills/restat-theory-model .opencode/skills/restat-theory-model && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "restat-theory-model" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Review-of-Economics-and-Statistics-Skills/skills/restat-theory-model into .opencode/skills/restat-theory-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "restat-theory-model", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
restat-theory-model- GitHub stars
- 1.2k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 594 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when deciding how much theory or structure a The Review of Economics and Statistics (REStat) manuscript should carry — right-sizing a model so it interprets or disciplines…
- Deciding how much theory
- SKILL.md covers When to trigger, The REStat theory bar, Decision: how much theory? and Right-sizing moves, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Structure a The Review of Economics and Statistics (REStat) manuscript should carry — right-sizing a model so it interprets
What it does
Restat Theory Model is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when deciding how much theory or structure a The Review of Economics and Statistics (REStat) manuscript should carry — right-sizing a model so it interprets or disciplines the empirical estimate without becoming the contribution. Calibrates the theory's role; it does not develop new theory for its own sake.
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Data & Analytics, covering Statistics. 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
- Deciding how much theory
- Structure a The Review of Economics and Statistics (REStat) manuscript should carry — right-sizing a model so it interprets
- Disciplines the empirical estimate without becoming the contribution
Example prompts
- “/restat-theory-model”
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
Restat Theory Model loads about 1.3k tokens when it runs. Until then it costs about 83 tokens; SKILL.md has 594 words of instructions outside code blocks.
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). 594 words, ~1,290 tokens.
Download SKILL.mdSave it as
.claude/skills/restat-theory-model/SKILL.md (or your agent's skills folder).- name
- restat-theory-model
- description
- Use when deciding how much theory or structure a The Review of Economics and Statistics (REStat) manuscript should carry — right-sizing a model so it interprets or disciplines the empirical estimate without becoming the contribution. Calibrates the theory's role; it does not develop new theory for its own sake.
Theory & Model Right-Sizing (restat-theory-model)
When to trigger
- A reduced-form result needs an economic interpretation a referee will ask for
- The draft has a sprawling model section that overshadows the empirical contribution
- You are unsure whether to estimate a structural model or stay reduced-form
- A referee asked "what is the mechanism?" or "what is the model behind this regression?"
The REStat theory bar
REStat is empirical-first: theory is in service of the estimate, not the headline. The right amount of model is the amount that (1) defines the estimand — names the parameter the design recovers and why it is interesting; (2) disciplines the interpretation — maps the coefficient to an economic object (an elasticity, a welfare-relevant margin, a structural parameter); or (3) delivers a counterfactual the reduced form cannot. Anything more risks turning the paper into a theory or pure-structural paper that belongs elsewhere. A short, transparent model that yields a testable prediction or an interpretable parameter is worth more at REStat than an elaborate one that buries the empirics.
Decision: how much theory?
| Situation | Theory dose | Form |
|---|---|---|
| Clean causal estimate of broad interest | Minimal | A paragraph mapping the coefficient to an economic object; estimand stated |
| Coefficient is ambiguous without a frame | Light model | A simple model giving a sign/comparative-static prediction the data test |
| Question demands a counterfactual / welfare number | Structural-light | A parsimonious model estimated/calibrated to deliver the counterfactual, validated out of sample |
| Mechanism is the contribution | Mechanism model + tests | Model that generates distinguishing predictions; test them against rival mechanisms |
| You want to publish the model itself | Wrong journal | Redirect to a theory/structural venue |
Right-sizing moves
- Lead with the estimand, not the equations. State the parameter the design identifies before any model algebra.
- Make every modeling assumption earn its place — if removing it does not change the interpretation, cut it.
- Tie structure to data features. If you estimate a structural parameter, name what in the data identifies it (hand to
restat-identificationBranch on measurement/identification logic). - Validate, don't just calibrate. Show fit to an untargeted moment when the model does real work.
- Keep the counterfactual honest. State the policy-invariance assumption a counterfactual relies on.
Show full SKILL.md (243 more words)Show less
Checklist
- The estimand is named and economically interpreted (elasticity / margin / structural parameter)
- Theory dose matched to the question (minimal / light / structural-light / mechanism)
- Every modeling assumption is load-bearing; non-essential ones cut
- If structural: identification of each parameter named; an untargeted moment validates fit
- If a counterfactual is run: policy-invariance / extrapolation assumptions stated
- The model does not overshadow the empirical contribution (page budget reflects priorities)
Anti-patterns
- A 10-page model section in front of a reduced-form paper — reads as a theory paper REStat will redirect
- Equations with no estimand stated, leaving the referee to guess what is identified
- A structural model calibrated, not validated, then used for a bold counterfactual
- Theory used decoratively (a model that predicts nothing the empirics test)
- Hiding a weak design behind structural machinery
Worked vignette: right-sizing a model to an estimate (illustrative)
A reduced-form paper finds that a transport-subsidy raised rural employment. A referee asks "what is the welfare implication?" — the reduced form alone cannot say. The wrong response is to bolt on a full spatial general-equilibrium model that takes over the paper. The right REStat response is a structural-light addition: a parsimonious model whose one new parameter (the commuting elasticity) is identified by the estimated employment response itself, validated against an untargeted moment (the change in commuting distance), and used to deliver a single welfare number with its uncertainty. The model earns exactly its keep — it converts the credible estimate into a welfare statement — without becoming the contribution.
Output format
【Theory role】define estimand | discipline interpretation | deliver counterfactual | model mechanism
【Theory dose】minimal | light | structural-light | mechanism-model
【Estimand】[parameter] = [economic object]; identified by [data feature]
【Counterfactual assumptions】[policy-invariance / extrapolation] — or "n/a"
【Cut】assumptions/sections removed as non-load-bearing: [...]
【Next step】restat-robustness© 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 Review-of-Economics-and-Statistics-Skills/skills/restat-theory-model of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Restat Theory Model 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Restat Theory Model this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Sandbox Benchvercel/next.js | 143k | — | ~4.1k | Automated safety check: Pass | MIT | |
| Statistical Analysisspacering-net/codeg | 3.9k | 3 repos | ~5k | Automated safety check: Pass | MIT | |
| StatsmodelszLanqing/codex-claude-academic-skills | 4.7k | 15 repos | ~4.9k | Automated safety check: Pass | BSD-3-Clause | |
| AI Daily DigestvigorX777/ai-daily-digest | 1.6k | — | ~1.3k | Automated safety check: Pass | None | |
| Statistical Powerspacering-net/codeg | 3.9k | 1 repos | ~3.6k | Automated safety check: Notes | MIT |
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Categories
Questions about Restat Theory Model
What does Restat Theory Model do?
A skill your agent uses when deciding how much theory or structure a The Review of Economics and Statistics (REStat) manuscript should carry — right-sizing a model so it interprets or disciplines…. Restat Theory Model is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when deciding how much theory or structure a The Review of Economics and Statistics (REStat) manuscript should carry — right-sizing a model so it interprets or disciplines the empirical estimate without becoming the contribution.
When should I use Restat Theory Model?
Restat Theory Model fits situations like: deciding how much theory; structure a The Review of Economics and Statistics (REStat) manuscript should carry — right-sizing a model so it interprets; disciplines the empirical estimate without becoming the contribution.
How do I install Restat Theory Model in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill restat-theory-model -a claude-code`. Or copy the skill folder (Review-of-Economics-and-Statistics-Skills/skills/restat-theory-model in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/restat-theory-model in your project. Claude Code loads it when a task matches its description.
How do I install Restat Theory Model in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill restat-theory-model -a codex`. Or copy the skill folder (Review-of-Economics-and-Statistics-Skills/skills/restat-theory-model in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/restat-theory-model in your project. Codex loads it when a task matches its description.
Can I use Restat Theory Model 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 restat-theory-model -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/restat-theory-model, .gemini/skills/restat-theory-model, .github/skills/restat-theory-model and .opencode/skills/restat-theory-model in your project.
What does Restat Theory Model need to run?
SKILL.md names no scripts, command-line tools or credentials: Restat Theory Model is instructions for the agent only.
Does Restat Theory Model 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 Restat Theory Model 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 Restat Theory Model use?
Restat Theory Model 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 Restat Theory Model use?
About 1.3k tokens (SKILL.md is roughly 5.2k 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 Restat Theory Model?
Skills that share tags, products or a category with Restat Theory Model: Sandbox Bench (vercel/next.js, 143k stars), Statistical Analysis (spacering-net/codeg, 3.9k stars), Statsmodels (zLanqing/codex-claude-academic-skills, 4.7k stars) and AI Daily Digest (vigorX777/ai-daily-digest, 1.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Restat Theory Model?
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.