meta-v2

SKILL效率
效率 未标注权限 许可证不明确
安装这个技能

Draft, restructure, or plan Nature-style manuscript sections from author-provided claims, results, figures, notes, or Chinese drafts. Use when the user wants to write or rebuild an abstract, introduction, related-work, method, experiments, discussion, conclusion, title, or full manuscript argument rather than only polish finished prose. Also trigger on general academic-writing requests even without the word "Nature", such as writing a paper from scratch, drafting a manuscript/section, structuring a paper, and Chinese phrasings like 学术写作、科研写作、论文写作、写论文、写paper、SCI写作、帮我写论文、搭论文框架、起草论文、写引言/摘要/讨论.

一句话选型结论

按资料字段整理

meta-v2是效率类的 Agent Skill,安装方式未标注,权限级别未标注,许可证不明确,有可直接复制的安装命令。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类效率 安装方式未标注 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 未标注 仓库 未标注
下载量 未标注 技能市场下载数
权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

未标注
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
skillhub install user_7d510643/skill-new-v2
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    执行上面的命令安装;也可以把仓库里的 SKILL.md 手动放进客户端的 skills 目录。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

效率
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方user_7d510643仓库 未标注 · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式未标注安装包 community
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验未标注上游最后核验时间 · 数据更新 1791729694
正文体量4.8 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
整理待办与日程

把零散任务收进清单,排出优先级。

批量处理重复任务

把固定动作做成模板,重复执行。

把流程写成清单

把口头流程整理成可复用的步骤。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 有可直接复制的安装命令,不用自己翻文档找入口。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在效率场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
meta-v2当前 未标注权限 未标注 未标注 未标注 有
Nano PDF 文档 联网访问 ClawHub 市场 424.9 万 OpenClaw 有
自动更新程序 浏览器控制 ClawHub 市场 296.4 万 OpenClaw 有
Gemini 助手 联网访问 ClawHub 市场 254.7 万 OpenClaw 有
word DOCX 文档 联网访问 ClawHub 市场 239.6 万 OpenClaw 有
Excel XLSX 前端 联网访问 ClawHub 市场 227.0 万 OpenClaw 有

SKILL.md 全文

4.8 KB
模型实际读到的说明书原文,来自技能仓库

Nature-Style Scientific Writing — Router

This skill is split into two layers:

  • A static layer under static/ that holds versioned, reusable content fragments (core stance + workflow, paper-type playbooks, per-section drafting guidance, language-specific rules, per-journal style).
  • A dynamic layer (this file plus manifest.yaml) that detects the request's axes and loads only the fragments needed for the current job.

Do not try to apply the drafting logic from memory or from this router. Always load fragments from disk as described below.

Routing protocol

Follow these five steps every time the skill is invoked.

1. Load the manifest and the core layer

Read manifest.yaml. It declares the axes (paper_type, section, language, journal), the allowed values, and the file paths each value maps to.

Also read every file listed under always_load. These hold the default stance, writing workflow, and output format that apply to every drafting job.

2. Detect the axis values for this request

For each axis in the manifest, decide the value using the manifest's detect: hint and the user's input:

  • paper_type — research / methods / hypothesis / algorithmic / review. Default: research.
  • section — abstract / intro / related-work / method / experiments / discussion / conclusion / title. May be multiple. Ask the user if it is ambiguous and matters for the draft.
  • language — en or zh-to-en. Detect from the user's notes themselves.
  • journal — nature / nat-comms / generic. Default: generic. If the user names a Nature subjournal, treat it as nature.

State the detected axis values in one short line to the user before drafting, so they can correct you cheaply.

3. Load the matching fragments

For each axis value, Read the file mapped in the manifest. Skip the section axis only when the user has explicitly asked for a free-floating argument paragraph with no section context.

Do not read every fragment in static/. Load only what step 2 selected.

4. Draft using the loaded material

Apply the loaded fragments in this priority order:

  1. Core stance + intake (core/stance.md) — surface missing claim / evidence / boundary before drafting.
  2. Paper-type playbook — argument chain, drafting order.
  3. Section-specific drafting rules and structure.
  4. Journal-specific framing and constraints.
  5. Language-specific sentence and paragraph rules (apply last).

Run the 8-step workflow in core/workflow.md end-to-end. Do not skip steps 1-3 (planning) just because the user asked for prose immediately — write the one-sentence argument first.

If essential evidence or boundary is missing, write a placeholder and list it under Assumptions or missing inputs: instead of inventing content.

5. Reach for references only when needed

The files under references/ are deep references and the example library, not defaults. Open them on demand per the references.on_demand table in the manifest. Typical triggers:

  • The user asks for a concrete example or template → references/examples/index.md.
  • A section's draft has structural problems that the section fragment alone does not explain → the matching references/<section>.md.
  • The user needs a broad-audience Nature abstract opening or asks about a summary paragraph → references/nature-summary-paragraph.md.
  • The user asks "does this paragraph flow?" → references/paragraph-flow.md.
  • The user asks for a self-review or rejection-risk audit → references/paper-review.md.

Why this split

  • The static layer is versioned and reviewable. Adding a new journal style, paper type, or section is one new file plus one manifest line.
  • The dynamic layer keeps each invocation cheap: only the fragments relevant to this draft enter context, instead of the full multi-thousand-line reference set.
  • The router itself is short on purpose. Update fragments, not this file, when adding scope.
  • This structure mirrors nature-polishing so shared content can later be lifted into a _shared/ layer used by both skills.

常见问题

5 问
答案由本站依据条目字段整理
meta-v2怎么安装?

在支持 Skills 的客户端里执行:skillhub install user_7d510643/skill-new-v2。安装方式为未标注。装完刷新技能列表或重开客户端。

meta-v2支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

meta-v2权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

meta-v2收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

meta-v2用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 未标注。