nsfc-qc

nsfc-qc is a skill for Claude Code, Codex from huangwb8/ChineseResearchLaTeX. It costs 152 tokens per session (1,986 once invoked), scanned A, original, MIT.

A read-only quality check for NSFC proposals, which are Chinese National Natural Science Foundation grant applications. It checks writing style, citation risks, length, structure, and clarity.

In plain words
What is it for?
Use it to produce a standardized quality-control report and structured findings about a LaTeX proposal.
Why use it?
It finds possible problems before editing or submission while leaving the proposal files unchanged.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Claude Code; mentions Codex.

Good fit Use it to produce a standardized quality-control report and structured findings about a LaTeX proposal.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/huangwb8/chineseresearchlatex/nsfc-qc
About the project

ChineseResearchLaTeX is a collection of LaTeX templates and an AI-assisted workflow for preparing Chinese research documents such as grant proposals, papers, theses, and academic CVs. Researchers use it to plan, format, review, compile, and revise these documents with human oversight. The catalogue skills and instructions support its agent-based research-writing workflow.

huangwb8/ChineseResearchLaTeX · 2,721 stars · on GitHub

Install

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.

Any agent
npx skills add huangwb8/ChineseResearchLaTeX --skill nsfc-qc
Clone the repo
git clone --depth 1 https://github.com/huangwb8/ChineseResearchLaTeX

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-qc

README.md
[![agentmods](https://agentmods.dev/badge/skills/huangwb8/chineseresearchlatex/nsfc-qc/github.svg)](https://agentmods.dev/skills/huangwb8/chineseresearchlatex/nsfc-qc)
Your own site
<a href="https://agentmods.dev/skills/huangwb8/chineseresearchlatex/nsfc-qc"><img src="https://agentmods.dev/badge/skills/huangwb8/chineseresearchlatex/nsfc-qc/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-qc

Your own site · 80×15
<a href="https://agentmods.dev/skills/huangwb8/chineseresearchlatex/nsfc-qc"><img src="https://agentmods.dev/badge/skills/huangwb8/chineseresearchlatex/nsfc-qc.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 152 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,986 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 $0.00152 $0.01986
Opus 5 $0.00076 $0.00993
Sonnet 5 $0.00030 $0.00397
Haiku 4.5 $0.00015 $0.00199

Measured 3d ago against content hash 8ffe6c771b22, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

nsfc-qc 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 3d ago.

The scan reads SKILL.md. This mod also ships 7 executable files (scripts/materialize_final_outputs.py, scripts/nsfc_qc_compile.py, scripts/nsfc_qc_precheck.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/nsfc-qc/SKILL.md · 163 lines

How it starts

The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.

NSFC 标书质量控制

  • 只读 QC:不修改 .tex/.bib/.cls/.sty
  • 目标是产出标准化 QC 报告,而不是“顺手帮用户改文”
  • 推荐布局:deliver_dir/ 放交付物,project_root/.bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/nsfc-qc/{run_id}/ 放工作区

输入

最少需要:

  • project_root

建议同时提供:

  • main_tex,默认 main.tex
  • threads,默认读 config.yaml
  • execution,默认 serial
  • deliver_dir,推荐显式给,便于实例隔离

非目标

  • nsfc-qc 不是编译检查工具。
  • PDF 能否编译成功属于环境/工程质量,不是本技能的核心交付。

流程

输入

按用户请求和配置文件提供必要输入;缺失信息应明确列出并停止依赖该输入的步骤。

执行步骤

  • 当用户环境中出现因本 skill 设计缺陷导致的 bug 时,优先使用 bensz-collect-bugs 按规范记录到 ~/.bensz-skills/bugs/,严禁直接修改用户本地 Claude Code / Codex 中已安装的 skill 源码。
  • 若 AI 仍可通过 workaround 继续完成用户任务,应先记录 bug,再继续完成当前任务。
  • 当用户明确要求“report bensz skills bugs”等公开上报动作时,调用本地 ghbensz-collect-bugs,仅上传新增 bug 到 huangwb8/bensz-bugs;不要 pull / clone 整个 bug 仓库。

定位 run 目录

  • 优先用实例隔离布局:
    • deliver_dir
    • workspace_dir=project_root/.bensz-api/task-{yyyymmdd-hhmm}-{简短描述}/nsfc-qc/{run_id}
    • run_dir={workspace_dir}
  • 只有用户明确要求 legacy 或处理旧产物时才读取 project_root/.nsfc-qc/

只读预检

  • 自动检测主 tex
  • 检查引用 key 是否存在
  • 检查 .bib 字段完整性
  • 生成引用证据包:Crossref / arXiv / Unpaywall 等 metadata + URL 可访问性 + title 比对
  • 输出篇幅分布、引号问题、缩略语与术语一致性初筛

多线程独立 QC

  • 优先用 parallel-vibe,并把 .parallel-vibe/ 放到当前 run 内部
  • snapshot 只包含最小必要副本:*.tex/*.bib + 预检证据包
  • 每个 thread 至少覆盖:
    • 文风与可读性
    • 引用真伪与错引风险
    • 篇幅与结构分布
    • 逻辑与论证闭环
    • 缩略语规范
    • 术语一致性
    • 至少 2 类其它 QC

汇总聚合

  • 主线程合并 threads 的 RESULT.md
  • 去重、冲突处理、按 P0/P1/P2 排序
  • 输出最小可执行修改路线

标准化报告

最终报告必须包含:

  1. 执行摘要
  2. 范围与只读声明
  3. 硬性问题(P0)
  4. 重要建议(P1)
  5. 可选优化(P2)
  6. 引用核查清单
  7. 篇幅与结构分布
  8. 建议的最小修改路线图
  9. 附录:复现信息
# 一键运行
python3 skills/nsfc-qc/scripts/nsfc_qc_run.py \
  --project-root projects/NSFC_Young \
  --main-tex main.tex \
  --deliver-dir projects/NSFC_Young/QC/vYYYYMMDDHHMMSS \
  --threads 5 \
  --execution serial

# 预检
python3 skills/nsfc-qc/scripts/nsfc_qc_precheck.py --project-root projects/NSFC_Young --main-tex main.tex --out <artifacts_dir> --resolve-refs

# 并行 QC
python3 skills/nsfc-qc/scripts/run_parallel_qc.py --project-root projects/NSFC_Young --run-id vYYYYMMDDHHMMSS --threads 5 --execution serial

# 物化 final 输出
python3 skills/nsfc-qc/scripts/materialize_final_outputs.py --project-root projects/NSFC_Young --run-id vYYYYMMDDHHMMSS

Read the full file on GitHub · 163 lines

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. 3d ago Changed · -5 lines 8ffe6c771b22
  2. 12d ago First seen · 168 lines · 152 tokens per session scan A cc61e1813f64

Subscribe to this mod's changes

nsfc-qc is a skill published in the GitHub repository huangwb8/ChineseResearchLaTeX (2,721 stars, last pushed 3d ago), licensed MIT. It adds 152 tokens to every session and 1,986 once invoked, about $0.0008 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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