nsfc-literature

nsfc-literature is a skill for Claude Code, Codex from Wesley-Yin77/nsfc_medicine_all. It costs 87 tokens per session (2,421 once invoked), scanned A, original, MIT.

A Chinese-language writing aid for the literature-review and rationale section of National Natural Science Foundation of China medical grant proposals. This section explains the research background, existing knowledge, gap, and reason for the proposed study.

In plain words
What is it for?
It is for drafting or structuring the proposal rationale and literature review across basic, clinical, preventive, pharmaceutical, or traditional Chinese medicine research.
Why use it?
It helps organize references and evidence into a clear step-by-step argument instead of a disconnected list of studies.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is 参见 `../nsfc-figure/static/core/figure-taxonomy.md` 的图类型分类。.

Good fit It is for drafting or structuring the proposal rationale and literature review across basic, clinical, preventive, pharmaceutical, or traditional Chinese medicine research.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/Wesley-Yin77/nsfc_medicine_all
agentmods
npx agentmods add skills/wesley-yin77/nsfc_medicine_all/nsfc-literature

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for nsfc-literature

README.md
[![agentmods](https://agentmods.dev/badge/skills/wesley-yin77/nsfc_medicine_all/nsfc-literature/github.svg)](https://agentmods.dev/skills/wesley-yin77/nsfc_medicine_all/nsfc-literature)
Your own site
<a href="https://agentmods.dev/skills/wesley-yin77/nsfc_medicine_all/nsfc-literature"><img src="https://agentmods.dev/badge/skills/wesley-yin77/nsfc_medicine_all/nsfc-literature/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for nsfc-literature

Your own site · 80×15
<a href="https://agentmods.dev/skills/wesley-yin77/nsfc_medicine_all/nsfc-literature"><img src="https://agentmods.dev/badge/skills/wesley-yin77/nsfc_medicine_all/nsfc-literature.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 87 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,421 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00087 $0.02421
Opus 5 $0.00044 $0.01210
Sonnet 5 $0.00017 $0.00484
Haiku 4.5 $0.00009 $0.00242

Measured 12d ago against content hash 94948f8fd002, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

nsfc-literature scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

nsfc-literature/SKILL.md · 161 lines

How it starts

The opening of the file, as written. The whole thing — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.

NSFC Literature — 立项依据撰写器

辅助撰写NSFC标书中最关键的"立项依据"部分,基于已中标标书的漏斗式递进范式。

Routing protocol

1. Load the manifest and core layer

Read manifest.yaml. Always load:

  • ../../../_shared/core/winning-patterns.md — 漏斗结构与中标模式
  • ../../../_shared/core/terminology.md — 术语一致性账本
  • ../../../_shared/core/ethics.md — AI辅助边界
  • static/core/stance.md — 默认立场

2. Detect axes

Axis Values Method
grant_type 面上 / 青年 / 地区 从用户描述检测
stage 大纲 / 草稿 / 终稿 从现有内容检测
discipline 基础医学 / 临床医学 / 预防医学 / 药学 / 中医药 从研究领域检测

3. Load matching fragments

  • grant_typestatic/fragments/grant_type/{面上,青年,地区}.md
  • disciplinestatic/fragments/discipline/{basic,clinical,preventive,pharmacy,tcm}.md

4. Apply the funnel framework

逐层构建立项依据的5层漏斗结构。【强制】必须分节!

⚠️ 核心铁律:22/22份中标标书的立项依据均采用分节递进结构。立项依据不能是一整块连续文字,必须用带编号的独立标题将内容拆分为4-6个小节。每节有一个明确的论证任务。

⚠️ 【强制检查项】前期工作基础分散渗透原则

前期工作基础/预实验数据必须分散在2-4节中作为论证证据,而非集中在一节用(1)(2)(3)(4)(5)Results式罗列。违反此原则会导致评审专家阅读疲劳,且显得像论文Results而非标书论证。

正确做法:每项前期发现以"问题引领"方式嵌入论证(如"CIP2A过表达的临床意义如何?为回答这一问题,申请人以..."),而非独立编号罗列。

错误做法:在某一节集中列出"(1)单细胞层面...(2)多队列层面...(3)表观组学层面..."的Results式清单。

⚠️ 【强制检查项】立项依据中的图类型规范

立项依据中只能放机制/通路示意图,不能放预实验数据组合图。预实验数据图(WB条带/统计图/散点图等)放在研究基础部分。

图编号 位置 允许的图类型 禁止的图类型
图1 Layer 2或3 信号通路图(已知通路+探索部分虚线标注) ❌ 预实验数据图
图2 Layer 3或4 机制示意图(核心分子功能,虚实线区分已知/待验证) ❌ 预实验数据图
图3 Layer 5末尾 机制假说图(全文假说总结,实线=已验证+虚线=拟验证) ❌ 预实验数据图

参见 ../nsfc-figure/static/core/figure-taxonomy.md 的图类型分类。

分节模板(强制使用)
立项依据
├─ 1. [疾病]的临床挑战与[领域]的研究现状
│    ├─ 流行病学数据(发病率/死亡率/现有治疗局限)
│    └─ 为什么要从[XX角度]研究该疾病
│
├─ 2. [核心领域/通路]在[疾病]中的研究进展
│    ├─ 该通路/领域的已知认知
│    ├─ 关键分子的已有功能证据
│    └─ ⚠ 此处开始引入1-2项预实验数据作为论据
│
├─ 3. [核心分子]在[疾病]中的功能与机制证据
│    ├─ 该分子的已知功能(基因→蛋白→通路→表型)
│    ├─ ⚠ 本课题组的前期发现(预实验数据2-3项)
│    └─ ⚠ 在此节中必须放置至少1张信号通路/机制示意图
│
├─ 4. [核心分子]调控[疾病]的潜在机制
│    ├─ ⚠ 更深入的机制层面分析和前期生信/实验数据
│    ├─ 已有证据的不足以回答关键问题
│    └─ ⚠ 在此节中放置第二张机制示意图或预实验数据图
│
└─ 5. 小结与科学假说
     ├─ 总结前文完整逻辑链
     ├─ "由此,我们提出如下科学假说:……"(必须用引号框出)
     └─ 简要验证策略 + 研究意义

Read the full file on GitHub · 161 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 161 lines · 87 tokens per session scan A 94948f8fd002

Subscribe to this mod's changes

nsfc-literature is a skill published in the GitHub repository Wesley-Yin77/nsfc_medicine_all (63 stars, last pushed 2mo ago), licensed MIT. It adds 87 tokens to every session and 2,421 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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