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Ai Paper Pipeline

该 Skill 将用户的论文想法或长工作流提示规范化:精简内容写入 SKILL.md,长文本放入 references/,模板放入 templates/;并可初始化论文项目脚手架(MEGA_PROMPT.md、RESTRICTS.yaml、PROGRESS.md、plans/、code/、data/、docs/、results/ 及 LaTeX 论文骨架)。强调不得虚构实验、数据、引用或结论,最…

hayashishungenn
hayashishungenn
热度 46.84
最近更新 2026-05-11 17:40:29
分类:效率依赖:读写文件 / 内部调用大模型应用场景:研究 / 工作流 / 模板

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add ai-paper-pipeline
Metadata
name
ai-paper-pipeline
description
Build or improve a top-tier AI conference paper workflow for NeurIPS, ICML, ICLR, and similar venues. Use when the user asks to generate a paper pipeline, organize a paper project, turn a mega prompt into a reusable skill, structure literature→experiment→writing loops, or create/update files like MEGA_PROMPT.md, RESTRICTS.yaml, PROGRESS.md, LaTeX paper skeletons, and per-stage plans for an academic paper project.

AI Paper Pipeline

Turn a rough paper idea or a long "mega prompt" into a reusable, reality-grounded paper project scaffold.

What this skill should do

  • Normalize a user's long paper-workflow prompt into a maintainable skill/project structure.
  • Keep the main workflow concise in SKILL.md and push bulky reference text into references/.
  • Preserve academic-integrity constraints: no fabricated experiments, no fake citations, no unsupported claims.
  • Prefer creating reusable project scaffolding over dumping one giant prompt blob.

Default workflow

  1. Identify whether the user wants one of these:
    • skill cleanup / packaging for the paper workflow itself
    • project initialization for a specific paper
    • template ingestion from a pasted mega prompt
  2. If the user pasted a large workflow prompt, extract and organize it into:
    • SKILL.md for concise usage instructions
    • references/ for long-form reference content
    • templates/ for starter files like RESTRICTS.example.yaml
  3. Keep only trigger logic, workflow guidance, and file navigation in SKILL.md.
  4. Put long source material, detailed prompts, and heavy policy text in references/.
  5. If the user wants a paper project initialized, create at minimum:
    • MEGA_PROMPT.md
    • RESTRICTS.yaml
    • PROGRESS.md
    • plans/
    • code/, data/, docs/, results/
    • paper/mypaper/main.tex
    • paper/mypaper/sections/
  6. After edits, package or commit changes if appropriate.

File layout for this skill

ai-paper-pipeline/
├── SKILL.md
├── MEGA_PROMPT.md
├── references/
│   ├── full-pipeline-template.md
│   └── project-scaffold.md
└── templates/
    └── RESTRICTS.example.yaml

When to read extra files

  • Read MEGA_PROMPT.md when you need the concise built-in version of the 25-stage workflow.
  • Read references/full-pipeline-template.md when the user wants the verbose original template or asks to reconstruct/port the full prompt.
  • Read references/project-scaffold.md when the user wants to initialize a concrete paper project directory.
  • Read templates/RESTRICTS.example.yaml when initializing a new paper project or drafting a restrictions file.

Working rules

  • Treat the paper as a real research artifact, not a vibe-writing exercise.
  • Never claim experiments, datasets, ablations, or statistical tests that are not actually present.
  • Never keep huge duplicated prompt text in multiple files.
  • Prefer editable project artifacts over giant single-message outputs.
  • Keep the paper workflow cyclical: literature → design → run → analyze → draft → review → revise.

Good outputs

A. User says: "整理成一个 Skill"

Do this:

  • Clean up the current skill folder.
  • Convert ad-hoc text into proper SKILL.md + references/ + templates/.
  • Keep SKILL.md concise and reusable.

B. User says: "按这个模板起一个论文项目"

Do this:

  • Create a new <project>-paper/ scaffold.
  • Copy in starter files.
  • Replace placeholders with project-specific metadata where provided.

C. User says: "把这份 mega prompt 落库"

Do this:

  • Save the raw template in references/ or project root.
  • Avoid bloating SKILL.md with the full raw text.

Final step

After modifying this skill or creating paper-project files in the workspace, commit the changes with a clear git message.