nsfc-benzi-audit
Use when a user wants applicant-facing diagnosis and revision advice on a Chinese NSFC (国自然) application draft — asks for 本子把脉, 本子体检, 国自然申请书修改建议, NSFC benzi audit, 帮我看国自然本子, 标书逻辑诊断, 青年/面上/地区基金申请书修改, 对照已中本子, 从中标样本提炼写法规律, 选题撞题核查, or 申请代码选得对不对 — or wants critique of the title, abstr
供给资产档案
研究与知识工作
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
场景
Document processing
I need my agent to read PDFs, extract tables, and turn documents into structured data.
适配 Agent
Claude Code + CLI + Codex
适用于 Codex、Claude Code、Cursor、CLI 或自定义 Agent。
安装
就绪
npx skills add jiankang1991/nsfc-benzi-audit --skill nsfc-benzi-audit
维护状态
新鲜
距上次推送 1 天
风险
需审查
The SKILL.md excerpt is truncated, but the provided content is sufficient to assess the skill's purpose and workflow.
GitHub 质量
46
63/100 质量 · 71/100 信任
覆盖标签
审查说明
The SKILL.md excerpt is truncated, but the provided content is sufficient to assess the skill's purpose and workflow. · The skill references external references (e.g., references/benzi-logic.md) that are not fully included in the excerpt, but this is expected for a multi-file skill.
Agent 采用评分卡
一眼查看信任、审计与安装准备度
这些分数综合公开仓库元数据、OpenAgentSkill 审查信号、维护新鲜度与安装准备度。它用于候选筛选,不替代人工审查。
质量
有潜力有用的候选项,但采用前应与替代方案比较。
信任
仅限沙盒有用但信任信号不足或混杂的候选项。在结果闭环证明任务匹配前,请保持在隔离工作区内使用。
审计
需审查对安装准备度、安全元数据、维护情况与采用风险的机器可读审查。
OpenAgentSkill 信任评分 v5
安装前需人工审查
仅在沙盒中运行,并在用于真实工作前比较接近的替代方案。
Stars
46 个 GitHub Stars
仓库活跃度
46 个 Star,5 个 Fork
维护状态
距上次推送 1 天
许可证
MIT
安装
npx skills add jiankang1991/nsfc-benzi-audit --skill nsfc-benzi-audit
安装安全性
标准软件包或运行时安装路径
权限范围
filesystem or document access, network or browser access
Agent 结果
暂未有 Agent 结果数据
文档
README/SKILL.md 上下文充分
风险摘要
生产前审查
- The SKILL.md excerpt is truncated, but the provided content is sufficient to assess the skill's purpose and workflow.
- Low GitHub adoption signal
- Quality score needs review
- GitHub adoption: 46 GitHub stars
安装准备度
安装路径可用
- 安装路径可用
- 仓库证据可用
- 已声明许可证
- 暂无 Agent 验证结果证据
Agent 可读元数据
这个 Skill 的机器可读决策数据。
使用此区块或内嵌 JSON 判断 Agent 是否应安装该 Skill、选择替代方案,或先请求人工审查。
适用任务
- Document processing 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
- Read uploaded files
适用 Agent
安装决策
- 命令
- npx skills add jiankang1991/nsfc-benzi-audit --skill nsfc-benzi-audit
- 策略
- 审查
- 人工审查
- 是
信任与风险
- 信任
- 63/100
- 审计
- 77/100
- 风险级别
- 需审查
结果闭环
- 端点
- /api/agent/outcome
- 事件 ID
- resolve
- 结果
- 5
不适用场景
- 需要厂商支持 SLA 的团队
- production agents without a repository review
- Low GitHub adoption signal
- The SKILL.md excerpt is truncated, but the provided content is sufficient to assess the skill's purpose and workflow.
- The skill references external references (e.g., references/benzi-logic.md) that are not fully included in the excerpt, but this is expected for a multi-file skill.
Agent 安全 v2
53/100 · 避免自动安装
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
中
Browser automation
Skill may drive a browser or interact with web pages.
中
网络访问
Skill 可能访问远程页面、API、仓库或外部服务。
中
文件系统访问
Skill 可能读取或写入项目文件、文档、生成产物或本地工作区状态。
中
数据库访问
Skill 可能检查 Schema、查询数据库或处理持久化存储。
- The SKILL.md excerpt is truncated, but the provided content is sufficient to assess the skill's purpose and workflow.
安装目标
在你的 Agent 工作流中安装此 Skill
通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install jiankang1991-nsfc-benzi-auditAgent 解析计划
让 Agent 在安装前验证匹配度。
Resolve API 返回首选 Skill、替代方案、安全策略、审计说明、安装目标和可直接执行的提示词,无需抓取此页面。
打开 JSON
/api/agent/resolve?task=Use%20nsfc-benzi-audit%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve 文本
/api/agent/resolve?task=Use%20nsfc-benzi-audit%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
安装交接
/api/skills/jiankang1991-nsfc-benzi-audit/install
Agent 应检查
- 从 Resolve API 检查任务匹配与替代方案。
- 检查审计评分、信任评分和安全策略警告。
- 检查 Codex、Claude Code、Cursor 或 CLI 的安装目标兼容性。
复制提示词
Task: Use nsfc-benzi-audit in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20nsfc-benzi-audit%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/jiankang1991-nsfc-benzi-audit/install
Install command: npx skills add jiankang1991/nsfc-benzi-audit --skill nsfc-benzi-audit
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent 交接
把安装路径交给 Agent,而不是再给一个目录页。
通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。
安装交接
/api/skills/jiankang1991-nsfc-benzi-audit/install
LLM 文本格式
/api/skills/jiankang1991-nsfc-benzi-audit/install?format=text
寻找替代方案
/api/skills/search?q=nsfc-benzi-audit&limit=3
Agent 提示词
Use nsfc-benzi-audit for this task. Review https://www.openagentskill.com/api/skills/jiankang1991-nsfc-benzi-audit/install, then install with: npx skills add jiankang1991/nsfc-benzi-audit --skill nsfc-benzi-auditRegistry 元数据
用于自动选择 Skill 的 Agent 可读档案。
本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号,让 Agent 无需抓取界面即可排序。
Agent 决策面板
Fallback candidate for Document processing
先用此 Skill 做原型验证,并保留备选方案。
栈中角色
备选候选
主要匹配
Document processing
信任标签
先做原型验证
安装路径
命令已就绪
适用场景
- Document processing 工作流
- Claude Code 团队
- builders willing to evaluate younger projects
证据
- 仓库近期活跃
- 已提供安装命令或 GitHub 仓库
- 63/100 质量档案
- 3 个 OpenAgentSkill 交互事件
先审查
- Low GitHub adoption signal
- The SKILL.md excerpt is truncated, but the provided content is sufficient to assess the skill's purpose and workflow.
实施路径
- 1在沙盒 Agent 中安装它,并端到端完成一次Document processing任务。
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
信任档案
仅限沙盒
有用但信任信号不足或混杂的候选项。在结果闭环证明任务匹配前,请保持在隔离工作区内使用。
GitHub 采用度
检查46 个 GitHub Stars
Star/Fork 活跃度
检查46 个 Star,5 个 Fork; 当前元数据中没有议题活跃度信息
近期维护
通过距上次推送 1 天
许可证清晰度
通过MIT
积极信号
- AI 审查已通过
- 安装路径可用
- 仓库证据可用
- 近期维护的仓库
- 安装命令未发现明显高风险模式
- 结果闭环已就绪,但需要首次真实 Agent 运行
安装前审查
- The SKILL.md excerpt is truncated, but the provided content is sufficient to assess the skill's purpose and workflow.
- Low GitHub adoption signal
- Quality score needs review
- GitHub adoption: 46 GitHub stars
- Stars/forks activity: 46 stars, 5 forks; issue activity unavailable in current metadata
- 暂未有真实 Agent 结果报告
- 无人值守安装前需要人工审查
建议操作
仅在沙盒中运行,并在用于真实工作前比较接近的替代方案。
质量档案
有潜力 适用于 Agent 工作流的候选
有用的候选项,但采用前应与替代方案比较。
工作流匹配
在这些场景使用此 Skill
Parse messy files
Document processing
I need my agent to read PDFs, extract tables, and turn documents into structured data.
Investigate faster
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
工作流匹配
加入完整工作流
Find, compare, and synthesize
Research report agent
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
RAG knowledge base
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Turn skills into distribution
Content growth agent
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
替代方案短名单
安装前对比
可能适合该任务的相近 Skill。
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Maigret
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Nuclei
Nuclei is a fast, customizable vulnerability scanner powered by the global security community and built on a simple YAML-based DSL, enabling collaboration to tackle trending vulnerabilities on the internet. It helps you find vulnerabilities in your applications, APIs, networks, DNS, and cloud configurations.
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Infisical is the open-source platform for secrets, certificates, and privileged access management.
概览
--- name: nsfc-benzi-audit description: Use when a user wants applicant-facing diagnosis and revision advice on a Chinese NSFC (国自然) application draft — asks for 本子把脉, 本子体检, 国自然申请书修改建议, NSFC benzi audit, 帮我看国自然本子, 标书逻辑诊断, 青年/面上/地区基金申请书修改, 对照已中本子, 从中标样本提炼写法规律, 选题撞题核查, or 申请代码选得对不对 — or wants critique of the title, abstract, key scientific questions, rationale, research contents, innovation, feasibility, research basis, 代表作/代表性论著 quality and support, or cross-section consistency. Accepts PDF/DOCX/Markdown/text or extracted draft text. This is applicant revision advice, not formal communication-review opinions; for expert review forms use nsfc-review. ---
# NSFC Benzi Audit
Use this skill to produce applicant-facing diagnosis and revision advice for NSFC application drafts. The goal is to expose logic breaks, weak scientific-question framing, mismatched sections, and high-impact fixes before submission.
Do not write a formal peer-review opinion unless the user explicitly asks for communication review; route that to `nsfc-review`. Do not fabricate facts, papers, project histories, budgets, or official rule details. Keep final advice grounded in the draft text and clearly mark uncertain extraction/OCR issues.
## Workflow
1. Locate and extract the draft. - For PDF input, use PDF extraction/OCR as needed. Prefer existing extracted Markdown such as `full.md` or `output.md` when available. - For DOCX input, extract text while preserving headings and tables where possible. - For extracted Markdown/text folders, prefer `output.md`, `full.md`, or the largest readable Markdown/text file; inspect images only when visual logic diagrams or tables matter. - If the file is scanned or extraction is noisy, state the limitation in the report and avoid treating OCR artifacts as applicant mistakes.
2. Identify the review scope before judging. - Extract project category, research attribute, application code, title, abstract, keywords, applicant/team context, and section boundaries. - If the user asks for a quick pass, inspect title, abstract, scientific questions, research contents, innovations, and research basis first. - If the user asks for full diagnosis, inspect the whole application by section.
3. Load the right references. - Always read `references/benzi-logic.md` before diagnosing logic or writing suggestions. - Read `references/audit-surfaces.md` for full diagnosis, structure/form checks, figure/readability checks, literature-current-status checks, or policy-risk triage. - Read `references/question-distillation.md` when judging how well the scientific question is distilled: the 关键科学问题 importance argument, the rationale's convergence chain, the 科学问题属性 justification, drafts claiming 原创/独辟蹊径/卡脖子/瓶颈/学科交叉, or when the user asks whether the 科学问题凝练得好. - Read `references/representative-works.md` when the draft lists 代表性论著/代表作/主要论文, or when 研究基础 leans on the applicant's publications. Do not judge those works from titles alone — get the abstract and method from the applicant's PDFs first, else via the `paper-lookup` skill, else mark them 未核实. - Read `references/kd-lookup.md` when the audit needs external evidence rather than draft-internal logic: 撞题/选题重复风险, 申请代码是否送对学部, 预期成果是否超额承诺, 申请人自己已资助/已结题项目的重复度与绩效, or a draft claiming 国内尚无人开展. The applicant runs the queries on kd.nsfc.cn; never automate its login or captcha, and never report a lookup result without the query string, hit count, and date. - Read `references/exemplar-learning.md` when the user provides already-funded/successful examples, asks to compare with "中的本子"/"中标本子", or asks to improve this skill from sample applications. - Read `references/information-communication.md` when the draft or provided examples involve information science, communication networks, optical networks, computer networks, data centers, remote sensing information processing, applied AI, network security, quantum communication, or related information-engineering directions. - Read `references/geospatial-remote-sensing.md` when the draft or provided examples involve remote sensing, GIS, geospatial intelligence, DEM/terrain/geomorphology, spatial databases, point clouds, SAR/optical/hyperspectral imagery, video GIS, camera networks, POI/trajectory/location data, city 3D modeling, or geospatial knowledge graphs. - Read `references/medical-biomedical.md` when the draft or provided examples involve medicine, clinical research, biomedicine, disease mechanisms, patient cohorts, specimens, animal/cell/organoid models, biomarkers, diagnostics, therapy/intervention, immunology, ethics, or biosafety. - Read `references/current-rules.md` when checking current-year compliance, research attributes, application-code risk, budget/ethics/scientific-integrity issues, or anything tied to official NSFC rules. - Use `assets/report-template.md` as the output shape unless the user requests another format.
4. If successful examples are provided, separate exemplar learning from target diagnosis. - Treat funded examples as pattern evidence, not as text to copy or proof of causality. - Anonymize names, project numbers, institutions, unpublished data, and sensitive achievements before extracting patterns. - Prefer patterns repeated across matched examples: same project type, similar discipline/application code, similar research attribute, or comparable career stage. - Apply exemplar patterns as contrastive questions: what does the target draft fail to make visible that successful examples make visible?
5. Build the one-page logic map. - Extract the draft's core logic elements: object/scenario, focused problem or goal, method/path, distinctive feature or innovation, and data/validation loop. - Extract the abstract logic chain: object/problem, method/goal, contents/innovation, achievement/significance. - Map these terms across title, abstract, rationale, research contents, scientific questions, innovation, feasibility, and research basis. - If a 科学问题属性 statement exists, map it too and check it cross-validates the key scientific questions. - Mark missing, vague, inconsistent, or duplicated elements.
6. Diagnose by priority, not by page order. - Lead with the three decisive funding factors (创新性、技术路线、前期研究基础) and the three scored axes (课题、申请人、研究条件); see `references/benzi-logic.md`. Because 会评 leans on 通讯意见 + title + abstract (see `references/current-rules.md`), weight title/abstract/通讯-facing clarity accordingly. - High priority: flaws likely to affect funding judgment, such as no real scientific question, engineering/technical task posing as basic research, object too broad, problem not focused, innovation unsupported, methods not tied to scientific questions, or research basis unrelated. - Medium priority: section-level weaknesses, such as literature review not pointing to proposed contents, research objectives not scientific enough, feasibility too generic, innovation phrased as slogans, required columns that may be missing, figures that do not match the text, or literature gaps that weaken the rationale. - Low priority: expression, structure, title length, repeated wording, formatting, and local polishing.
7. Give concrete revision actions. - For every major finding, cite the draft section or quoted phrase briefly, explain why it is a problem, and give an actionable fix. - Prefer rewrite recipes and replacement skeletons over generic advice. - When suggesting rewritten text, label it as a draft example that the applicant must verify against facts and literature.
8. Output a Markdown report. - Default filename: `本子诊断报告.md` next to the source draft when working in files; otherwise answer in chat. - Include: overall judgment, one-page logic map, prioritized fixes, section-by-section findings, structure/form checks, figure/readability checks, data/validation evidence mapping, representative-works support (when listed), funding-landscape/topic-collision checks (when kd lookups were run), literature checks, consistency matrix, candidate rewrites, official-rule status, and limits. - If successful examples were used, include a short exemplar-derived pattern section with transferability limits. - Do not paste long extracted source text. Quote only short phrases needed to support findings.
## Style
- Write in simplified Chinese unless the user asks otherwise. - Be direct, specific, and applicant-facing: "建议将..." rather than "评审认为..." unless simulating review. - Separate "must fix before submission" from "can polish later". - Avoid empty comments such as "加强创新性"; say which scientific question, mechanism, model, method, experiment, or evidence must be changed. - Preserve academic integrity: do not invent literature, data, publications, patents, collaborations, preliminary results, or official policy requirements. - Do not copy distinctive wording, structure, data, or undisclosed ideas from successful examples into another applicant's draft.
技术详情
- 版本
- 1.0.0
- 许可证
- MIT
- 最近更新
- 2026年8月21日
- 发布时间
- 2026年8月21日
决策摘要
备选候选
仓库近期活跃
Agent 验证证据
Agent 验证证据
来自解析、审查、安装和一次小范围运行后的结果报告。
- 成功率
- —
- 近期失败
- —
- 结果
- 0
- 输出质量
- —
- 失败
- 0
- 不相关
- 0
- 安装次数
- 0
- 风险拦截
- 0
- 需要配置
- 0
- 生产环境
- 0
暂时没有 Agent 结果数据。首次 Agent 执行可以通过 /api/agent/outcome 报告成功、需要设置、风险拦截、失败或不相关。
增长闭环
分享工具包
为 nsfc-benzi-audit 准备的场景化草稿,可手动发布到 X。
nsfc-benzi-audit: Use when a user wants applicant-facing diagnosis and revision advice on a Chinese NSFC (国自然)... 46 stars https://www.openagentskill.com/skills/jiankang1991-nsfc-benzi-audit?ref=x
可选:带安装命令的回复
Listing + install path for nsfc-benzi-audit: https://www.openagentskill.com/skills/jiankang1991-nsfc-benzi-audit?ref=x Install: npx skills add jiankang1991/nsfc-benzi-audit --skill nsfc-benzi-audit
收录来源
Registry 收录
此列表来自公开来源,维护者认领获批前不会标记为官方。
- 创作者
- jiankang1991
- 收录方
- OpenAgentSkill 社区索引
归属链接指向公开仓库或创作者主页。创作者可认领列表以更新所有权信号。
认领此 Skill所有者认领
认领此 Skill 页面
这条 Registry 收录 列表归属于 jiankang1991,但尚未标记为官方。认领后可增加已验证所有者信号,使后续发布、安装和审计更新更值得信赖。
创作者外链工具包
将证据徽章加入你的 README
在开发者评估仓库的位置展示规范页面、当前信任与审计信号,以及真实的 Agent 验证证据。
[](https://www.openagentskill.com/skills/jiankang1991-nsfc-benzi-audit)
[](https://www.openagentskill.com/skills/jiankang1991-nsfc-benzi-audit)
[](https://www.openagentskill.com/skills/jiankang1991-nsfc-benzi-audit/audit)
[](https://www.openagentskill.com/skills/jiankang1991-nsfc-benzi-audit)作者
jiankang1991
@jiankang1991
平台适配
健康信号
- GitHub Stars
- 46
- 质量评分
- 35/100
- 最近 GitHub 推送
- 2026年8月21日
- 框架提示
- 未知
- OpenAgentSkill 浏览量
- 3
- 复制安装命令
- 0
- 跳转点击
- 0
社区信号
告诉我们这个 Skill 是否对你的 Agent 工作流有帮助。汇总反馈会持续改善排序。
信任与安全
仅限沙盒
- GitHub 采用度46 个 GitHub Stars检查
- Star/Fork 活跃度46 个 Star,5 个 Fork; 当前元数据中没有议题活跃度信息检查
- 近期维护距上次推送 1 天通过
- 许可证清晰度MIT通过
- README/SKILL.md 完整度元数据包含足够的用法与工作流上下文通过
- 依赖与运行时风险公开元数据中未发现主要依赖风险提示通过
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