Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add HuiyuLi-2000/Chinese-Grant-Writer-Skills --skill fund-background-writergit clone --depth 1 https://github.com/HuiyuLi-2000/Chinese-Grant-Writer-SkillsWrote 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.
[](https://agentmods.dev/skills/huiyuli-2000/chinese-grant-writer-skills/fund-background-writer)<a href="https://agentmods.dev/skills/huiyuli-2000/chinese-grant-writer-skills/fund-background-writer"><img src="https://agentmods.dev/badge/skills/huiyuli-2000/chinese-grant-writer-skills/fund-background-writer/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.
<a href="https://agentmods.dev/skills/huiyuli-2000/chinese-grant-writer-skills/fund-background-writer"><img src="https://agentmods.dev/badge/skills/huiyuli-2000/chinese-grant-writer-skills/fund-background-writer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00047 | $0.01641 |
| Opus 5.5 | $0.00019 | $0.00656 |
| Sonnet 5.5 | $0.00009 | $0.00328 |
| Haiku 4.5 | $0.00005 | $0.00164 |
Grade A, and why
fund-background-writer 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
fund-background-writer
基于 16 本成功 NSFC 申请书提炼的写作范式，实现"主题分析 → 政策调研 → 数据调研 → 立项依据撰写"的自动化流程。
技能范围
本技能只负责 NSFC 申请书中立项依据的 1.1 研究意义 部分，包含：
- 研究背景（含国家战略、现实困境、学术问题、本项目方案）
- 理论意义
- 实践意义
触发条件
当用户要求撰写 NSFC 立项依据、研究意义、项目背景，或提供研究主题并要求生成立项依据时，激活本技能。
执行流程
收到用户提供的材料后，严格按以下 7 步执行：
用户至少会提供以下输入：研究内容、研究方法、技术路线、特色与创新、研究目标、关键科学问题。如果输入不足，必须先追问补全再继续。
Step 1：读取知识库
读取以下文件，学习写作范式：
assets/templates/writing_style_guide.md—— 风格规范和叙事逻辑assets/templates/structure_template.md—— 段落安排和句子逻辑角色
Step 2：主题分析
- 解析研究主题的核心关键词
- 识别所属学科领域（管理科学与工程 / 医学 / 经济学 / 信息科学等）
- 确定科学问题属性（鼓励探索 / 聚焦前沿 / 需求牵引 / 交叉融通）
Step 3：输入-背景锚定
映射原则：让 agent 知道背景的每一段要"指向"什么，确保逻辑贯通。锚定是逻辑层面的"影子对应"，不是文字层面的"复制粘贴"——背景中的困境/不足/方案要用背景自己的语言和论证视角来写，但逻辑上要能追溯到后续输入。
输入→段落映射表：
| 用户输入 | 对应背景段落 | 写作视角转换 |
|---|---|---|
| 研究内容 | 段落C 的困境条数 | "现实问题"视角，不用"研究内容"视角 |
| 研究方法细节 | 段落D 的不足条数 | "现有方法的局限"视角，不用"本研究方法"视角 |
| 技术路线 | 段落E 的方案展开顺序 | 浓缩为"做什么"不说"怎么做"，用"本项目拟……" |
| 特色与创新 | 理论意义的条目 | 创新点说"做了什么"，理论意义说"有什么学术价值" |
| 研究目标 | 实践意义的条目 | 研究目标说"要实现什么"，实践意义说"对社会/行业有什么价值" |
| 关键科学问题 | 段落F 的科学问题列举 | 进行轻微改写，但不要直接复制，且与后续输入表述接近合理 |
独立约束：段落A和B（政策背景+数据背景）不受后续输入约束，由联网检索结果决定。
Step 4：联网检索
按以下策略执行联网搜索（由 agent 自行选择可用工具）：
政策检索（详见 references/policy_search_strategy.md）
- 优先来源：国务院、科技部、NSFC、国家统计局、教育部、国家卫健委、工信部、国家发改委及研究主题对应主管部门
- 目标：找到 2-3 个与主题直接相关的国家/部门级政策文件
- 记录：政策名称、发布年份、核心要求/表述
数据检索（详见 references/data_search_strategy.md）
- 优先来源：国家统计局、行业蓝皮书、权威白皮书、国际组织报告、高水平综述
- 目标：找到 3-5 个支撑问题严重性的统计数据
- 记录：年份 + 具体数值 + 出处 + 原始链接
- 禁止使用营销文章、无来源数据、转载数据
Step 5：生成立项依据大纲
按 structure_template.md 的段落结构，生成大纲：
- 每段标注：写什么、用什么数据/政策、句子逻辑角色
- 确保问题-方案一一对应
- 向用户展示大纲，确认后进入撰写
Step 6：撰写完整立项依据
严格遵循 writing_style_guide.md 的风格规范：
- 按段落 A→B→C→D→E→F → 理论意义 → 实践意义的顺序撰写
- 每段确保有政策/数据支撑
- 理论意义用"动词+对象+价值"结构分点阐述
- 实践意义从宏观到微观层层递进
- 避免"首次""填补空白"等绝对化表述
- 方法术语只做背景/验证手段，不撑段落主线
Step 7：自检与输出
- 按
references/dod_checklist.md检查结构完整性 - 按
references/boastful_expression_guidelines.md排查浮夸表达 - 按
references/dimension_coverage_design.md检查四个维度覆盖 - 输出最终文本，同时附上：
- 使用的政策清单（政策名称 + 年份 + 核心表述）
- 使用的统计数据清单（数据项 + 年份 + 数值 + 出处 + 链接）
What ships with it
13 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.
- assets/templates/structure_template.md 8.3 KB
- assets/templates/writing_style_guide.md 11 KB
- config.yaml 3.5 KB
- references/boastful_expression_guidelines.md 1.7 KB
- references/data_search_strategy.md 3.8 KB
- references/dimension_coverage_design.md 1.0 KB
- references/dod_checklist.md 1.7 KB
- references/info_form.md 2.4 KB
- references/methodology_term_examples.md 1.1 KB
- references/policy_search_strategy.md 3.0 KB
- references/scientific_hypothesis_guidelines.md 2.2 KB
- references/scientific_question_guidelines.md 2.0 KB
- references/theoretical_innovation_guidelines.md 2.1 KB
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.
- 2mo ago First seen · 117 lines · 47 tokens per session scan A 05d91068c74d
fund-background-writer is a skill published in the GitHub repository HuiyuLi-2000/Chinese-Grant-Writer-Skills (493 stars, last pushed 4mo ago), licensed MIT. It adds 47 tokens to every session and 1,641 once invoked, about $0.0002 per session on Opus 5.5. 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.
fund-background-writer compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| fund-background-writerHuiyuLi-2000/Chinese-Grant-Writer-Skills | Skill | 493 | 4mo ago | MIT | A | 47 | Claude Code, Codex |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | 2d ago | Apache-2.0 | A | 123 | Claude Code |
| exploratory-data-analysisK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 83 | Claude Code |
| matlabK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 44 | Claude Code |
| phylogeneticsK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 71 | Claude Code, Codex |
| research-engineerdavila7/claude-code-templates | Skill | 33k | yesterday | MIT | A | 43 | Claude Code, Codex |
| mapping-to-snomedmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 205 | Claude Code |