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paper-card-analyzer

Analyze `paper-parse` outputs and generate a research-oriented paper card directly in natural language. Use this skill after paper parsing when you need a structured summary of contributions, method, experiments, limitations, reproducibility notes, and future work without running any extra script.

chen-li-170 来源安装数☆ 0 仓库 Stars

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。

SkillHub CLI

skillhub install chen-li-17/paper-card-analyzer

打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

Paper Card Analyzer

Generate a research-oriented paper-card from paper-parse results using direct natural-language analysis.

Input Expectations

Read artifacts produced by paper-parse:

  • *_content.md (full parsed paper content in markdown)
  • *_parsed.json (metadata and figures)

Output

Produce the paper card in English by default, with balanced depth, and always save outputs in the same folder as the selected *_content.md and *_parsed.json.

Always save:

  • paper-card.md
  • paper-card.json
  • paper-card-feedback.md (feedback log and revision history)

The generated card uses this fixed section order:

  1. Paper Snapshot
  2. Research Problem and Motivation
  3. Core Contributions
  4. Method Overview
  5. Experimental Setup
  6. Main Results and Evidence
  7. Ablation and Analysis Findings
  8. Limitations and Threats to Validity
  9. Reproducibility Notes
  10. Open Questions and Future Work

Workflow

  1. Identify the target pair of files:
    • Preferred: one *_content.md and one *_parsed.json in the same folder.
    • If multiple candidates exist, ask user to pick one pair.
  2. Read parsed metadata from *_parsed.json:
    • title, paper_name, num_pages, figures.
  3. Read *_content.md and extract evidence by section:
    • abstract/introduction/method/experiments/results/ablation/limitations/conclusion.
  4. Write a research-oriented card:
    • Prioritize scientific novelty, methodological logic, evidence strength, validity threats, and reproducibility.
  5. Save first draft to the same folder:
    • paper-card.md and paper-card.json.
  6. Request human feedback and revise:
    • Ask what to correct, expand, or make stricter.
    • Update card and save again (overwrite current files).
    • Append each round to paper-card-feedback.md with: round number, user request, key edits.
  7. Repeat revision rounds until the user explicitly confirms satisfaction.
  8. Keep uncertainty explicit:
    • If a section is missing, say "Not clearly stated in parsed...

来源信息

Source
github
Repository
openclaw/skills
Path
skills/chen-li-17/paper-card-analyzer
Version
—
Commit
d8d05f2d8eb30b08841f9b8fd24d9f3579b8cbfc
分类来源
rules
状态
active
可见性
public

这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。

来源内容

SKILL.md
# Paper Card Analyzer

Generate a research-oriented `paper-card` from `paper-parse` results using direct natural-language analysis.

## Input Expectations

Read artifacts produced by `paper-parse`:

- `*_content.md` (full parsed paper content in markdown)
- `*_parsed.json` (metadata and figures)

## Output

Produce the paper card in English by default, with balanced depth, and always save outputs in the same folder as the selected `*_content.md` and `*_parsed.json`.

Always save:

- `paper-card.md`
- `paper-card.json`
- `paper-card-feedback.md` (feedback log and revision history)

The generated card uses this fixed section order:

1. Paper Snapshot
2. Research Problem and Motivation
3. Core Contributions
4. Method Overview
5. Experimental Setup
6. Main Results and Evidence
7. Ablation and Analysis Findings
8. Limitations and Threats to Validity
9. Reproducibility Notes
10. Open Questions and Future Work

## Workflow

1. Identify the target pair of files:
   - Preferred: one `*_content.md` and one `*_parsed.json` in the same folder.
   - If multiple candidates exist, ask user to pick one pair.
2. Read parsed metadata from `*_parsed.json`:
   - `title`, `paper_name`, `num_pages`, `figures`.
3. Read `*_content.md` and extract evidence by section:
   - abstract/introduction/method/experiments/results/ablation/limitations/conclusion.
4. Write a research-oriented card:
   - Prioritize scientific novelty, methodological logic, evidence strength, validity threats, and reproducibility.
5. Save first draft to the same folder:
   - `paper-card.md` and `paper-card.json`.
6. Request human feedback and revise:
   - Ask what to correct, expand, or make stricter.
   - Update card and save again (overwrite current files).
   - Append each round to `paper-card-feedback.md` with: round number, user request, key edits.
7. Repeat revision rounds until the user explicitly confirms satisfaction.
8. Keep uncertainty explicit:
   - If a section is missing, say "Not clearly stated in parsed...

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