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Agent Skill · 研究检索

nature-article-writer(自然文章作家)

nature-article-writer 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

nature-article-writer 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 63,725。

总安装 312周安装 13GitHub Stars 公开资料未说明下载 104核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:nature-article-writer(自然文章作家)
来源仓库:https://github.com/tristanmanchester/agent-skills
仓库路径:skills/nature-article-writer
安装命令:
npx skills add https://github.com/tristanmanchester/agent-skills --skill nature-article-writer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/tristanmanchester/agent-skills --skill nature-article-writer

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息,支持自然主题文章的素材收集与整理。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景获取候选结果。通过 npx 安装,需确认权限范围和维护状态,注意潜在的联网或文件访问行为。建议结合来源仓库和原始 README 核验具体功能与使用限制。

nature-article-writer 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/nature-article-writer

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/tristanmanchester/agent-skills --skill nature-…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

nature-article-writer 怎么安装?

在终端执行 npx skills add https://github.com/tristanmanchester/agent-skills --skill nature-article-wr…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

nature-article-writer 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

nature-article-writer 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

nature-article-writer 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

nature-article-writer 用的人多吗?

公开数据是累计安装 312 次,近一周安装 13 次,下载 104 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

nature-article-writer 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
nature-article-writer

自然文章作家 · 本页

312—只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Nature Article Writer

Write and revise primary research manuscripts so they feel editorially mature: precise, proportionate, detailed where detail matters, and genuinely pleasurable for a scientist to read. Beautiful Nature-style prose is not ornate prose. It is clear, load-bearing prose with strong logic, good sentence movement, and no wasted claims.

This skill optimises for editorial quality, reader trust, and human-sounding scientific prose. It does not optimise for AI-detector evasion.

Do not imitate a named living author. Emulate journal expectations, the user's own prior writing if supplied, and the specific paper's evidence profile.

When to activate this skill

Use this skill when the user:

  • names Nature or a Nature Portfolio journal
  • asks for "Nature-style", "Nature journal", or "high-impact journal" scientific writing
  • wants a title, summary paragraph, abstract, introduction, results, discussion, methods, figure legend, presubmission package, cover letter, or reviewer response
  • wants a scientific draft to sound more natural, less generic, less formulaic, or less obviously machine-written
  • wants to convert notes, figures, bullet points, or a rough draft into a submission-ready manuscript
  • wants a diagnostic pass on manuscript structure, claim calibration, prose quality, or compliance

Success standard

A strong output from this skill should feel like it was written by a careful scientist-editor who understands both the data and the journal:

  • the central claim is evident early and never overstated
  • adjacent-field readers can follow the logic without drowning in jargon
  • each paragraph has a job
  • each sentence earns its place
  • results progress by question and answer, not lab chronology
  • the prose is varied but restrained
  • limitations are surfaced before reviewers must drag them out
  • end matter and policy-sensitive statements are present or explicitly marked as missing

Non-negotiables

  • Never invent data, methods, figures, ethics approvals, accession numbers, references, software versions, statistical results, or journal-specific limits.
  • Never strengthen a claim beyond the evidence actually supplied.
  • Never hide uncertainty. Mark missing facts explicitly with [confirm], [insert ref], [insert accession], or a short Issues to confirm list.
  • Never use AI-generated figures or image content for publication.
  • Never copy distinctive phrasing from published papers. Use exemplars for structure, rhythm, and level-setting, not sentence theft.
  • If AI did more than copy editing, remind the user to check whether disclosure is required under the target journal's policy. Human authors remain accountable for the final text.

Default workflow

1. Build the manuscript brief

Infer or assemble the minimum brief:

  • target journal and content type
  • one-sentence central claim
  • why it matters outside the immediate subfield
  • evidence ladder: 3-6 concrete results, figures, or analyses that support the claim
  • strongest prior work and the precise gap
  • strongest limitation or boundary condition
  • data, code, and materials availability
  • ethics or compliance facts if humans, animals, clinical samples, or sensitive data are involved

If the user has scattered notes, use assets/manuscript-brief-template.md.

2. Calibrate before you draft

Use both of these calibration layers when possible.

A. Journal calibration

Consult references/modes.md and references/journal-calibration.md.

  • Choose the closest bundled mode:

- nature-article - nature-letter - portfolio-article - portfolio-letter

  • If the user names a specific journal and web access is available, verify the live guide and inspect 2-4 recent primary research papers from that journal.
  • Build a short internal style card: title texture, opening-paragraph shape, heading policy, legend density, end-matter order, and how aggressively claims are hedged.
B. Exemplar anchoring

If the user supplies their own accepted papers, lab style guides, or a high-quality draft they want to sound like, use references/exemplar-anchoring.md and optionally run:

python3 scripts/prose_fingerprint.py --candidate draft.md --reference exemplar1.md exemplar2.md --format text

Imitate broad habits such as sentence length range, paragraph density, degree of overt signposting, and tolerance for technical detail. Do not imitate distinctive turns of phrase.

3. Build the editorial architecture

Before line-level drafting, create:

  • a one-sentence paper promise
  • a figure-claim matrix
  • a paragraph map for the major sections

Use:

This is the main upgrade over a generic "write the paper" prompt. The prose improves when the structure is load-bearing before wording starts.

4. Draft in evidence order, not display order

Default drafting order:

  1. figure plan and one-sentence take-home message for each figure
  2. Results
  3. Methods
  4. Discussion or concluding synthesis
  5. opening context paragraph or Introduction
  6. summary paragraph or abstract
  7. title
  8. figure legends
  9. availability statements and other end matter
  10. cover letter or presubmission material if requested

Starting from figures and claims produces more grounded prose than starting from the title or abstract.

5. Shape paragraphs deliberately

Every paragraph needs:

  • a topic sentence that names the paragraph's job
  • evidence or reasoning that advances the job
  • a final stress position that lands the important point or hands the reader to the next paragraph

Use references/sentence-craft.md and assets/paragraph-map-template.md. Prefer old-to-new information flow, concrete verbs, and sentences that end on the point that matters.

6. Run a human-voice pass tuned for scientific prose

Consult references/voice-and-variation.md.

Target common instruction-tuned LLM artefacts without turning the paper chatty:

  • overuse of present-participial clause chains
  • noun-heavy nominalized phrasing
  • conveyor-belt transitions (Additionally, Moreover, Importantly, Taken together)
  • inflated significance language
  • generic concluding sentences that claim importance without stating the implication
  • repeated weak sentence openings (This, These, It, We)
  • flat sentence rhythm and uniform paragraph shape

Do not blindly ban passive voice, repetition, or technical compounds. Scientific prose needs all three sometimes. The aim is selective repair.

7. Run integrity and compliance checks

Use references/integrity-and-compliance.md and, if Python 3 is available:

python3 scripts/nature_preflight.py --input draft.md --mode nature-article --format text

or the relevant mode:

python3 scripts/nature_preflight.py --input draft.md --mode portfolio-article --format text

Use the report to fix:

  • title length and title texture
  • missing required or expected sections
  • opening paragraph length or structure
  • missing Data Availability or Code Availability sections
  • bracket citations that need conversion
  • figure legends missing title sentences or statistical detail
  • hype words, generic AI-ish phrases, rhythm flatness, or repeated weak openers
  • obvious overclaim or unsupported forward-looking claims

If scripting is unavailable, do the same checks manually.

Section guidance

Use references/section-rubric.md for detailed section-by-section repair rules. High-level rules:

Title

  • clear, searchable, and readable outside the narrow subfield
  • avoid hype, puns, slogans, rhetorical questions, and vague grandeur
  • for main Nature, aim for roughly 75 characters and avoid numbers, acronyms, abbreviations, and punctuation unless essential

Summary paragraph or abstract

  • broad context first, then the specific gap
  • state the main finding once, cleanly
  • end on the most defensible implication
  • use references in main Nature-style summary paragraphs when appropriate
  • avoid stuffing it with data scraps, acronyms, or methodological clutter

Introduction or opening

  • move quickly from field context to unresolved problem
  • do not write a mini-review
  • finish with what the paper does, why the approach is appropriate, and what kind of answer the paper delivers

Results

  • organise by conceptual question or figure logic, not by when experiments happened
  • make every subsection claim-bearing
  • distinguish observation from interpretation
  • mention only the numbers that advance the story

Discussion

  • say what the work establishes, what it suggests, and where it stops
  • surface the main limitation before the reviewer does
  • end with the most defensible field-level implication, not a cinematic future vision

Methods

  • concise but genuinely informative
  • include the details that govern interpretability and reproducibility
  • use short subsection headings and concrete labels

Figure legends

  • begin with a brief title sentence
  • describe panels in sequence
  • define statistics, sample sizes, centre values, and error bars where relevant
  • stand on their own as far as reasonable

Working modes

A. Full manuscript from notes

Deliver:

  • a short manuscript brief
  • a figure-led blueprint
  • the full draft in the chosen template
  • an unresolved-gap list
  • optional preflight and fingerprint reports

B. Rewrite an existing draft

Process:

  1. identify the actual claim
  2. preserve data and meaning
  3. repair structure
  4. line-edit for Nature-style clarity and reader movement
  5. flag claims that need verification

C. Abstract or summary paragraph only

Where useful, provide 2-3 versions:

  • conservative
  • balanced or default
  • slightly bolder but still defensible

Label the trade-off in claim strength.

D. Reviewer response or rebuttal

Use assets/reviewer-response-template.md.

Rules:

  • answer every point directly
  • quote the reviewer briefly, then answer
  • specify exactly what changed and where
  • concede valid points plainly
  • when declining a request, explain why and offer the nearest rigorous alternative

E. Presubmission enquiry or cover letter

Use:

Write for editors, not reviewers. Explain:

  • the central advance
  • why broad readers should care
  • why the evidence is strong enough
  • why the paper fits this journal
  • what the paper is not claiming

Output style

When returning a draft or rewrite:

  • state the chosen journal mode and key assumptions
  • give the manuscript in clean, journal-ready prose
  • include a brief Issues to confirm list only when necessary
  • do not pad the answer with generic writing advice unless the user asked for it

When returning diagnostics:

  • prioritise the 5-10 issues that will most improve reader trust and editorial fit
  • separate structural issues from line-edit issues
  • suggest concrete rewrites, not vague criticism

Fast heuristics for excellent Nature-style prose

  • A clear limitation usually makes the paper sound stronger.
  • If a phrase could appear in almost any paper, cut or replace it.
  • The sentence ending matters. Land on the point that earns emphasis.
  • Replace abstract importance language with the exact implication.
  • Good scientific prose can be vivid without being promotional.
  • Detail is welcome when it is the detail that lets the reader trust the claim.
  • "Human sounding" here means precise, calm, varied, and specific, not casual.

Bundled references

Bundled assets

平台分布

Codex

35.51%
按下载量换算37

Claude

30.83%
按下载量换算32

Cursor

17.04%
按下载量换算18

Gemini CLI

9.55%
按下载量换算10

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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