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Dyz Med Key Literature

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duyunzhoudyz
dyz-med-key-literature

从已有候选文献池中筛选前沿、奠基、指南、系统综述、矛盾证据和本土关键文献,完成全文级结构化精读并形成 可复用的文献地图、单篇简报和证据综合。当用户要“精读几篇关键论文”“找绕不开的文献”或核对与结论矛盾的 研究时使用;从零检索文献应先用 dyz-med-cnki,只有摘要或题录时不得声称已完成深度精读。 Use for critical appraisal and synthesis of available full-text medical literature.

Overview

Publisherduyunzhoudyz
Repositorydyz-med-paper-skills
Skill namedyz-med-key-literature
Stars
102
Forks
1
Bundled files
4
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by duyunzhoudyz on GitHub. Read the source before you install it.

Installation

Install the Dyz Med Key Literature AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/duyunzhoudyz/dyz-med-paper-skills/tree/main/dyz-med-key-literature
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/duyunzhoudyz/dyz-med-paper-skills.git /tmp/dyz-med-paper-skills
mkdir -p .claude/skills
cp -r /tmp/dyz-med-paper-skills/dyz-med-key-literature .claude/skills/dyz-med-key-literature
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dyz Med Key Literature in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Dyz Med Key Literature on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Dyz Med Key Literature is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

关键文献筛选与精读

核心原则

  • 本技能从候选池开始,不重复承担完整检索。
  • “重要”由与研究问题的关系、证据角色和方法质量共同决定,不只看被引数或期刊名。
  • 矛盾证据、阴性结果和方法学局限必须保留。
  • 单篇研究记录研究设计和偏倚风险;GRADE 用于证据体确定性,不给单篇论文机械贴 GRADE 等级。
  • full_text_read 必须对应实际可访问并已核对的全文。
  • 不绕过付费墙、登录、版权或机构权限。

输入

优先接收:

  • 来自 dyz-med-cnki 的候选文献表或用户提供的 RIS、BibTeX、CSV、PMID、DOI 清单;
  • 研究问题、PICO/PECO/PCC 和拟支持的论断;
  • 本地 PDF、合法开放全文或用户已获授权的资料;
  • 中国人群或本土实践场景下的中文来源覆盖说明。

若没有候选池,先调用 dyz-med-cnki。若只有少量明确论文,可直接进入核实与精读。

工作流程

1. 核实候选记录

对每条记录核对:

  • 标题、作者、年份、期刊;
  • PMID、DOI 或其他稳定标识符;
  • 研究设计、目标人群和主要问题;
  • 当前访问状态;
  • 来源及检索日期。

仅网页片段或二手清单发现的记录先标为 discovery_only。

可消费 dyz-med-cnki 题录核验器的独立回执,不强制导入兄弟脚本或创建passport:以稳定工件ID、真实 path/version/sha256定位输入,检查scope、execution_status、mode、逐字段差异和报告哈希。 reference_identity: matched/mismatch/unverified仅说明该次字段比较;offline matched是固定响应重放, 不是本次联网核实。题录字节/版本改变后旧报告不得沿用,completed或工具退出0不证明研究质量、全文已读 或论断SUPPORTED。API元数据只记metadata_only,不要把仅取得题录写成读过摘要或全文。

真DOI配错题名应保留mismatch并人工查证;404、429、超时、缺DOI或无结果仅为未核实,不据此判虚构。 既有有效外部核验记录可直接使用,不为接入工具重复检索。需要外部处理时先核对公开内容类别、用途、 固定接收方、允许发送字段和当前人类授权;未知则零发送,在本地继续。最小标识符核验不授权发送稿件或全文。

2. 分级排序

优先选择能承担以下角色的文献:

角色选择重点
frontier最近出现的新方法、新结果或新争议
landmark奠定定义、机制、设计或临床实践的核心研究
guideline当前指南、共识或官方标准
synthesis高质量系统综述或 meta 分析
contradictory与主流或本研究方向不一致的证据
methods_borrow可借鉴结局定义、混杂控制、模型或报告方式
local_context中国人群、国内实践、政策或本土流行病学

被引数只能作为辅助信号,并记录数据来源和查询日期。

3. 获取与记录全文

按以下顺序尝试:

  1. 用户提供或项目已有的本地 PDF;
  2. 期刊、PubMed Central、机构仓储或其他合法开放来源;
  3. 用户有权访问的机构资源;
  4. 无法获取时记录 access_failure_recorded,请求用户补充。

涉及中文医学、护理或国内实践时,应尝试覆盖 CNKI、万方、维普或用户指定来源。无法直接访问时:

  • 记录每个来源的实际尝试与限制;
  • 由 dyz-med-cnki 生成 discovery_only 线索;
  • 请求用户通过合法账号或图书馆补充全文;
  • 不把网页线索描述为三库完整检索,也不伪造“零结果”。

4. 深度精读

对每篇选中文献核对全文中的:

  • 研究问题和设计;
  • 人群、样本、暴露或干预、比较和结局;
  • 方法、统计模型和关键假设;
  • 主要结果、效应量与不确定性;
  • 偏倚风险、缺失数据、局限性和资金/利益冲突;
  • 与当前稿件可支持和不可支持的论断;
  • 可借鉴的方法与不可直接迁移的条件。

有文档解析工具时,可用目录、分节阅读和表格提取提高效率;工具不可用时人工阅读本地全文。摘要不能支持的细节不得补写。

5. 建立文献层

项目模式下生成:

  • paper/evidence/key-literature-map.yaml;
  • paper/evidence/key-paper-briefs/*.md;
  • paper/evidence/frontier-literature-synthesis.md;
  • paper/evidence/fulltext-ledger.yaml;
  • 需要时生成 paper/evidence/literature-source-coverage.yaml。

非项目模式可直接交付同等结构的 Markdown,不强制创建文件。

单篇简报至少包含:

  • 可核实标识符与访问状态;
  • 研究设计和研究问题;
  • 方法与关键结果;
  • 风险偏倚和局限;
  • 对当前稿件的用途;
  • 不能由该文献支持的论断。

6. 综合

前沿综合分开呈现:

  • 支持性证据;
  • 矛盾或阴性证据;
  • 方法学借鉴;
  • 本土与国际证据差异;
  • 仍未解决的缺口;
  • 对引言、方法和讨论的具体影响。

不得因文献与预期结论不一致而降低其优先级。

完成检查

  • 候选记录的 PMID、DOI 或来源已核实;
  • 每篇选中文献有明确选择理由;
  • full_text_read 对应实际存在并已核对的全文;
  • 每篇全文级文献有结构化简报;
  • 摘要级记录没有被当作全文证据;
  • 单篇论文没有被错误赋予 GRADE 证据体等级;
  • 矛盾证据、局限和访问失败已披露;
  • 综合明确说明对当前稿件可支持与不可支持的论断。

配套资源

  • templates/key-literature-tracking-table.md:精读进度与证据角色追踪表。
  • examples/worked-example.md:虚构教学示例。
  • references/规范与文献清单.md:证据评价与引用原则参考。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Dyz Med Key Literature AI skill do?

从已有候选文献池中筛选前沿、奠基、指南、系统综述、矛盾证据和本土关键文献,完成全文级结构化精读并形成 可复用的文献地图、单篇简报和证据综合。当用户要“精读几篇关键论文”“找绕不开的文献”或核对与结论矛盾的 研究时使用;从零检索文献应先用 dyz-med-cnki,只有摘要或题录时不得声称已完成深度精读。 Use for critical appraisal and synthesis of available full-text medical literature.

Why use Dyz Med Key Literature on TypingMind?

Because you install it once and use it with any model. Dyz Med Key Literature is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Dyz Med Key Literature in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/duyunzhoudyz/dyz-med-paper-skills/tree/main/dyz-med-key-literature. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Dyz Med Key Literature?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Dyz Med Key Literature?

As many as you like. As long as a model supports skills, you can use Dyz Med Key Literature with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Dyz Med Key Literature AI skill free?

It is published on GitHub by duyunzhoudyz. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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