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

Lancet Writing

ASecurity

Use to structure and hold the length of a Lancet Article main text — Introduction, Methods, Results, Discussion (~3000–3500 words), the Research in context panel, a limited reference list (~30), and a cautious, globally minded Discussion that does not overstate.

1,052 stars
0 votes
0 copies
0 views
Added 6/5/2026
ai-agentsgo

Works with

cli

Security Analysis

A100/100

Scanned 6/5/2026

Install to Claude Code

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

Installs into .claude/skills of the current project.

Are you the author of Lancet Writing?

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

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

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

Download with Pro
Files
SKILL.md
---
name: lancet-writing
description: Use to structure and hold the length of a Lancet Article main text — Introduction, Methods, Results, Discussion (~3000–3500 words), the Research in context panel, a limited reference list (~30), and a cautious, globally minded Discussion that does not overstate.
---

# Main-Text Writing & Structure (lancet-writing)

## When to trigger

- Drafting or trimming a Lancet original-research **Article**.
- The main text is over length, or the Discussion overstates the findings.
- The structure wanders (lab/clinic chronology instead of IMRaD).
- Co-authors keep adding paragraphs and references and the paper is creeping past budget.

## Article structure (IMRaD + the panel)

The Lancet original-research **Article** uses standard **IMRaD** with the Research in context panel:

| Section | Holds |
|---------|-------|
| **Introduction** | The problem, the gap, and the specific objective — brief (the systematic search lives in the panel, not a long literature review). |
| **Methods** | Design, setting/countries, participants, randomisation/allocation/blinding (or observational design), outcomes, sample size, statistical analysis (pre-specified), registration, ethics. Methods are detailed and **stay in the main text** (clinical journals expect full Methods, unlike Science's supplement model). |
| **Results** | Recruitment/flow (with the flow diagram), Table 1, primary outcome, secondary outcomes, subgroups, harms — in a logical order. |
| **Discussion** | Principal findings → comparison with other studies → strengths and limitations → implications. |
| **Research in context panel** | The mandatory three-part box (see `lancet-research-in-context`). |

## Length and reference budget

- **Main text ~3000–3500 words** (Articles; confirm the current cap — formats and limits change).
- **References limited (~30)** for an Article — cite the key and the systematic-search-anchored literature, not everything.
- Tables/figures within the journal's display-item allowance (see `lancet-figures-tables`); extended methods/results → appendix.
- An **appendix / supplementary material** carries the protocol summary, additional analyses, full subgroup tables, and the reporting checklist.

## The Discussion — four moves, cautiously

Write the Discussion in this order, and keep it cautious:

1. **Principal findings** — restate the main result plainly, without re-listing every number.
2. **Comparison with other studies** — situate against prior evidence (consistent with the panel's systematic search); explain agreement/disagreement.
3. **Strengths and limitations** — be candid; name confounding, generalisability, missing data, power.
4. **Implications** — for practice, policy, and research, with calibrated causal language.

> The Lancet prizes **caution, not overstatement**. Match claims to design: an observational study shows association, not causation; a single trial rarely "proves" — it "supports" or "provides evidence for." A non-inferiority trial cannot claim superiority.

## House style

- Accessible, globally minded prose: avoid US-only framing; define context for an international readership; spell out abbreviations on first use.
- British spelling is the house style; use the journal's conventions for numbers, units (SI), and dates.
- Lead Results paragraphs with the clinical finding, then the supporting statistics.

## Output format

```
【Sections present】 Introduction / Methods / Results / Discussion / Research-in-context panel — all? yes/no
【Methods in main text?】 yes (good) / pushed to appendix (FIX)
【Main-text word count】 N → over/under ~3000–3500 by M
【Reference count】 N → vs ~30 budget
【Discussion four moves】 principal findings / comparison / strengths-limitations / implications — all? yes/no
【Overstatement check】 causal language calibrated to design? yes/no
【Next】 lancet-ethics
```

## Anti-patterns

- **Do not** write a long literature-review Introduction — the systematic search belongs in the panel.
- **Do not** overstate: no causal claims from observational designs, no "proves," no superiority claim from a non-inferiority trial.
- **Do not** let the Discussion re-list Results numbers instead of interpreting them.
- **Do not** blow the reference budget by citing exhaustively; cite the load-bearing literature.

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', ...

686011 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 →