Skills DirectorySkills Directory
SkillsLearnSecurityCategoriesDocsCommunityBlog
Sign InSubmit Skill
Skills Directory

Security-tested agent skills for Claude, coding agents, and AI workflows.

Directory

  • Browse Skills
  • All Skills A–Z
  • Claude Skills
  • Claude Code Skills
  • Agent Skills
  • Categories
  • Authors
  • Submit a Skill

Learn

  • Learn Hub
  • Install Claude Skills
  • Write SKILL.md
  • Skills vs MCP
  • Directories Compared

Security

  • Security
  • Methodology
  • Secure Claude Skills
  • Security Badges

Company

  • About
  • Community
  • Blog
  • API Docs
  • Advertise

2026 Skills Directory. All rights reserved.

ProTermsPrivacyRefunds
Back to skills

Qe Writing Style

ASecurity

Use when polishing prose, abstract, and introduction for a Quantitative Economics (QE) manuscript so a quantitative method and its economic payoff land for a general-interest Econometric Society readership. Reflects QE house rules (no significance asterisks; report SEs/coverage sets). Polishes exposition; it does not change results or estimation.

1,052 stars
0 votes
0 copies
0 views
Added 6/6/2026
ai-agents

Security Analysis

A100/100

Scanned 6/6/2026

Install to Claude Code

$npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill qe-writing-style --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Qe Writing Style?

Add the live security badge to your README — it updates automatically with every re-scan.

Security grade badge for Qe Writing Style
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/brycewang-stanford-qe-writing-style/badge)](https://www.skillsdirectory.com/skills/brycewang-stanford-qe-writing-style)

More formats (shields.io, HTML) on the badges page.

Download with Pro
Files
SKILL.md
---
name: qe-writing-style
description: Use when polishing prose, abstract, and introduction for a Quantitative Economics (QE) manuscript so a quantitative method and its economic payoff land for a general-interest Econometric Society readership. Reflects QE house rules (no significance asterisks; report SEs/coverage sets). Polishes exposition; it does not change results or estimation.
---

# Writing Style (qe-writing-style)

## When to trigger

- The prose buries the economic question under method or notation
- The abstract describes the topic but never states what was found or built
- The introduction reaches the model/estimator before the reader sees the question
- Statistical claims lean on asterisks or vague intensifiers instead of magnitudes and uncertainty

## QE house style: a quantitative method serving a substantive question

QE is read across all of economics through an **Econometric Society** lens, so a paper must make **both** the substantive economic question **and** the quantitative apparatus (structural model, estimator, experiment, or simulation) legible to a smart non-specialist early. Format facts that shape the writing: the **abstract is ≤150 words**; the title page carries keywords and affiliations; the manuscript is **1.5/double-spaced, ≥12pt, ≤32 lines per page**, with figures and tables **in-text**. Crucially, QE's **house rules forbid asterisks and boldface for statistical significance** — the prose and exhibits must communicate findings through **point estimates with standard errors and confidence/coverage sets**, so write magnitudes and uncertainty into the sentences themselves. QE also applies its own reference style at copyediting, so keep citations consistent rather than chasing a format.

## The introduction arc (QE template)

1. **The question** — one or two sentences, plain language, stakes clear.
2. **Why it is hard quantitatively** — the measurement, identification, or computational obstacle.
3. **The approach** — the data + model/estimator/experiment that resolves it, in one paragraph.
4. **The headline result** — the key estimate or quantity, with units **and a standard error / coverage set**, stated early.
5. **Mechanism & interpretation** — what it means; the economic frame in a sentence.
6. **Contribution & lesson** — placement in the literature + what transfers beyond this setting.
7. **Roadmap** — brief.

## Abstract: state the finding (≤150 words)

- Open with the question and the approach in one breath, then **state the result with a number and its uncertainty**.
- For structural/computational work, name the quantity (an elasticity, a welfare number, a counterfactual) and the model that delivers it.
- Close with the broad lesson. No throat-clearing; stay within 150 words.

## Sentence-level craft

- Active voice; short declaratives for the key claims.
- Define notation once; do not make the reader hold five symbols to parse a sentence.
- Quantify with uncertainty ("a 7.3% rise, s.e. 1.1") rather than "significantly affects" or asterisks.
- Calibrated confidence reads as competence; hedge only where the evidence requires it.
- Relocate heavy derivations and extra results to the Supplemental Appendix (≤25 pages); the main paper stays self-contained.

## Checklist

- [ ] Abstract states the actual finding with a number **and** its uncertainty, ≤150 words
- [ ] The question is on page one in plain language
- [ ] The headline estimate appears early in the intro, with units and a standard error / coverage set
- [ ] The broad lesson ("beyond this setting") is explicit
- [ ] No significance asterisks or boldface in prose or exhibits
- [ ] Magnitudes are quantified, not vaguely intensified
- [ ] Notation introduced once; references consistent (QE styles at copyediting)

## Anti-patterns

- An abstract that names the topic but never the result, or runs past 150 words
- Leading the intro with the estimator ("We use indirect inference...") instead of the question
- Reporting significance with asterisks/boldface (QE forbids this)
- Vague magnitude language ("significantly", "substantially") with no number or uncertainty
- Notation overload in the introduction

## Output format

```
【Abstract verdict】states finding + number + uncertainty, ≤150 words? [Y/N] — fix: ...
【Intro arc】question / hardness / approach / result / interpretation / contribution present? [Y/N each]
【Headline estimate in intro】present + units + SE/coverage? [Y/N]
【Significance reporting】asterisk-free, SEs/coverage shown? [Y/N]
【Broad lesson stated】[Y/N]
【Next step】qe-replication-and-data-policy or qe-review-process
```

Attribution

brycewang-stanfordbrycewang-stanford
View sourceMore from brycewang-stanford →
SSkills DirectorySkills Directory

Your tool, in front of Claude Code builders.

3 founder slots · $299/mo · GSC-verified traffic · sponsors can never buy grades.

See placements

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments (0)

No comments yet. Be the first to comment!

SSkills DirectorySkills Directory

Your tool, in front of Claude Code builders.

3 founder slots · $299/mo · GSC-verified traffic · sponsors can never buy grades.

See placements

Related Skills

Caveman

Ultra-compressed communication mode that cuts output tokens while keeping technical accuracy. Levels: lite, full, ultra and the wenyan variants. Use for /caveman, "caveman mode", "talk like caveman", "be brief" or "less tokens".

1066601 votes

Hyperplan

Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...

693161 votes

Mcp Code Execution

Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.

3351 votes

catchup

Recovers the conversation and failed tool calls of a previous Codex, Claude Code, Antigravity, Cline, Copilot CLI, Cursor, DeepSeek Harness, Kimi, OpenCode, Pi Agent, or ZCode session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", asks to recover/summarize a previous session before continuing, or asks to diagnose or report a catchup failure. Do NOT use for the current conversation, git history, or any non-agent log.

651 votes

math-skill

A comprehensive mathematical reasoning skill for AI assistants — handles arithmetic to research-level problems with rigorous step-by-step reasoning, systematic verification, and transparent uncertainty handling

381 votes
View all in ai-agents →