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Agent Skill · 研究检索

academic-tone-guide(学术语气指南)

academic-tone-guide 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。

academic-tone-guide 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 72,863。

总安装 186周安装 8GitHub Stars 209下载 65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:academic-tone-guide(学术语气指南)
来源仓库:https://github.com/wentorai/research-plugins
仓库路径:skills/academic-tone-guide
安装命令:
npx skills add https://github.com/wentorai/research-plugins --skill academic-tone-guide
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/wentorai/research-plugins --skill academic-tone-guide

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。

学术语气指南用于调整学术写作的语调、语域和表达风格,使其符合学科规范和目标刊物的惯例。适用于需要从非正式草稿到发表级文稿之间进行语体转换的研究者或写作者。通过提供学科特定的风格建议、模糊化语言使用及常见语调误区提示来优化文本。安装前请确认权限范围、维护状态,以及是否会触发联网或文件读写操作。

建议结合原始 README 和仓库内容进一步核验具体用法和功能边界。

来源仓库内路径:skills/academic-tone-guide

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/wentorai/research-plugins --skill academic-ton…;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

academic-tone-guide 怎么安装?

在终端执行 npx skills add https://github.com/wentorai/research-plugins --skill academic-tone-guide。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

academic-tone-guide 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。

academic-tone-guide 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。

academic-tone-guide 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。

academic-tone-guide 用的人多吗?

公开数据是累计安装 186 次,近一周安装 8 次,下载 65 次,GitHub 209 星。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。

academic-tone-guide 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
academic-tone-guide

学术语气指南 · 本页

186209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

Academic Tone Guide

A skill for adjusting the tone, register, and voice of academic writing to match disciplinary expectations and target venue conventions. Covers the spectrum from informal drafts to publication-ready prose, including hedging language, impersonal constructions, discipline-specific stylistic norms, and common tone pitfalls that undermine credibility.

Understanding Academic Register

The Register Spectrum

Academic writing occupies a specific position on the formality spectrum. The appropriate register depends on the genre (journal article, conference paper, thesis, grant proposal, blog post) and the discipline (humanities tend toward more elaborate prose; STEM fields favor concise, direct statements).

Register Levels in Academic Writing:

Level 1 - Informal (lab notebooks, internal emails):
  "We tried the new method and it worked way better."

Level 2 - Semi-formal (conference talks, blog posts):
  "We tested the proposed method and observed significant improvement."

Level 3 - Formal (journal articles, theses):
  "The proposed method was evaluated against the baseline, yielding
   a statistically significant improvement in accuracy (p < 0.01)."

Level 4 - Highly formal (legal briefs, policy documents):
  "The aforementioned methodology was subjected to rigorous
   evaluation, the results of which demonstrate a statistically
   significant enhancement in predictive accuracy."

Most academic papers should aim for Level 3. Level 4 often sounds stilted and impedes readability. Level 2 is acceptable for workshop papers or invited commentaries but too casual for top-tier journals.

Discipline-Specific Norms

STEM Fields:
  - Prefer active voice for methods: "We collected samples..."
  - Use passive voice for established processes: "Samples were centrifuged..."
  - Short sentences, minimal adjectives
  - Precision over elegance
  - Numbered equations and defined variables

Social Sciences:
  - Mix of active and passive voice
  - Moderate hedging: "The results suggest..." rather than "The results prove..."
  - Theory-heavy introductions with clear operational definitions
  - APA style typically required

Humanities:
  - Complex sentence structures are acceptable
  - Argumentative, first-person voice common in many fields
  - Extensive engagement with prior scholarship expected
  - Discipline-specific jargon must be deployed precisely
  - Chicago or MLA style common

Hedging and Boosting

Hedging Language

Hedging is the use of cautious language to qualify claims. It signals intellectual honesty and awareness of limitations. Over-hedging weakens arguments; under-hedging invites criticism.

Hedging Devices:

Modal verbs (strength order):
  might < could < may < can < should < would < will < must
  "This approach might explain..."  (weak claim)
  "This approach may explain..."    (moderate claim)
  "This approach can explain..."    (confident claim)

Hedging phrases:
  "It appears that..."
  "The evidence suggests..."
  "One possible interpretation is..."
  "To some extent..."
  "Under certain conditions..."

Hedging quantifiers:
  "Most participants..." (not "all")
  "In many cases..." (not "always")
  "A substantial proportion..." (not "everyone")

When to Hedge and When Not To

HEDGE when:
  - Reporting your own results (findings suggest, data indicate)
  - Making causal claims from correlational data
  - Generalizing beyond your sample
  - Interpreting ambiguous results
  - Discussing implications and future directions

DO NOT HEDGE when:
  - Stating established facts ("DNA is a double helix")
  - Describing your own methodology ("We recruited 200 participants")
  - Reporting objective measurements ("The temperature was 37 degrees C")
  - Citing published findings ("Smith (2020) demonstrated that...")

Common Tone Problems and Fixes

Informal Language

Problem: Colloquialisms and contractions

Before: "We didn't find any significant results, which was kind of
         surprising given that lots of previous studies had found
         strong effects."

After:  "No statistically significant effects were observed, a finding
         that contrasts with the robust effects reported in prior
         studies (Smith et al., 2019; Jones, 2020)."

Rules:
  - No contractions (didn't -> did not, it's -> it is)
  - No colloquialisms (kind of, a lot, pretty much)
  - No rhetorical questions in formal papers
  - Avoid first-person opinion statements without evidence
  - Replace vague quantifiers with specific numbers

Overconfident Claims

Problem: Making claims stronger than the evidence supports

Before: "Our results prove that social media causes depression in
         teenagers."

After:  "Our results indicate a significant positive association
         between social media usage and depressive symptoms among
         adolescent participants, consistent with the hypothesis
         that excessive social media engagement may contribute to
         negative mental health outcomes."

Note: "Prove" is almost never appropriate in empirical research.
      Use "demonstrate," "indicate," "suggest," or "support."

Emotional Language

Problem: Using emotionally charged words that bias the reader

Before: "The appalling lack of research on this devastating condition
         is shocking and must be remedied immediately."

After:  "Despite the substantial disease burden, the existing literature
         on this condition remains limited. Further research is needed
         to address critical knowledge gaps."

Authorial Voice and Person

First Person Usage

The question of whether to use "I" or "we" in academic writing varies by discipline and journal.

Active first person (increasingly accepted in STEM):
  "We designed the experiment to test..."
  "We propose a novel framework for..."
  "In this paper, we argue that..."

Passive alternative:
  "The experiment was designed to test..."
  "A novel framework is proposed for..."
  "This paper argues that..."

Guidance:
  - Check your target journal's style guide
  - "We" is standard in multi-author papers, even in passive-heavy fields
  - Single-author "I" is common in humanities, less so in STEM
  - Avoid "the authors" to refer to yourself (awkward in most contexts)
  - Never use "you" to address the reader in formal papers

Practical Revision Checklist

Tone Audit Checklist:

1. Search for contractions -> expand all
2. Search for colloquialisms -> replace with formal equivalents
3. Check hedging on all claims -> calibrate to evidence strength
4. Verify consistent voice (active/passive) -> match journal norms
5. Remove emotional/judgmental adjectives -> use neutral descriptors
6. Check for rhetorical questions -> convert to declarative statements
7. Ensure technical terms are defined on first use
8. Verify that "significant" always means "statistically significant"
9. Remove filler phrases ("it is important to note that") -> state directly
10. Read abstract aloud -> does it sound like published papers in the venue?

This checklist can be applied during the final revision pass, after substantive content editing is complete. Tone adjustments should be among the last changes made, as earlier revisions frequently introduce new informal language that needs to be caught.

平台分布

Codex

37.57%
按下载量换算24

Claude

28.15%
按下载量换算18

Cursor

19.83%
按下载量换算13

Gemini CLI

9.3%
按下载量换算6

安全审计

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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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