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WILLOSCAR

agent-survey-corpus

by WILLOSCAR

Research pipelines as semantic execution units: each skill declares inputs/outputs, acceptance criteria, and guardrails. Evidence-first methodology prevents hollow writing through structured intermediate artifacts.

83🍴 10📅 Jan 24, 2026

SKILL.md


name: agent-survey-corpus description: | Download a small corpus of open-access arXiv survey/review PDFs about LLM agents and extract text for style learning. Trigger: agent survey corpus, ref corpus, download surveys, 学习综述写法, 下载 survey. Use when: you want to study how real agent surveys structure sections (6–8 H2), size subsections, and write evidence-backed comparisons. Skip if: you cannot download PDFs (no network) or you don't want local PDF files. Network: required. Guardrail: only download arXiv PDFs; store under ref/ and keep large files out of git.

Agent Survey Corpus (arXiv PDFs → text extracts)

Goal: create a small, local reference library so you can learn from real agent surveys when refining:

  • C2 outline structure (paper-like sectioning)
  • C4 tables/claims organization
  • C5 writing style and density

This is intentionally not part of the pipeline; it is an optional, repo-level toolkit.

Inputs

  • ref/agent-surveys/arxiv_ids.txt

Outputs

  • ref/agent-surveys/pdfs/
  • ref/agent-surveys/text/
  • ref/agent-surveys/STYLE_REPORT.md (tracked; auto-generated summary)

Workflow

  1. Edit ref/agent-surveys/arxiv_ids.txt (one arXiv id per line).
  2. Run the downloader to fetch PDFs and extract the first N pages to text.
  3. Skim the extracted text under ref/agent-surveys/text/:
    • look at section counts (H2), subsection granularity (H3), and how they transition between chapters.
    • identify repeated rhetorical patterns you want the pipeline writer to imitate.

Script

Quick Start

  • python .codex/skills/agent-survey-corpus/scripts/run.py --help
  • python .codex/skills/agent-survey-corpus/scripts/run.py --workspace . --max-pages 20

All Options

  • --workspace <dir> (use . to write into repo root)
  • --inputs <semicolon-separated> (default: ref/agent-surveys/arxiv_ids.txt)
  • --max-pages <N> (default: 20)
  • --sleep <seconds> (default: 1.0)
  • --overwrite (re-download + re-extract)

Examples

  • Download/extract into repo root ref/:
    • python .codex/skills/agent-survey-corpus/scripts/run.py --workspace . --max-pages 20
  • Download/extract into a specific folder (treated as workspace root):
    • python .codex/skills/agent-survey-corpus/scripts/run.py --workspace /tmp/surveys --max-pages 30

Troubleshooting

  • Download fails / timeout: rerun with a larger --sleep, or try fewer ids.
  • Text extract is empty: the PDF may be scanned; try another survey or increase --max-pages.
  • Files showing up in git status: PDFs/text are ignored via .gitignore (ref/**/pdfs/, ref/**/text/).

Score

Total Score

70/100

Based on repository quality metrics

SKILL.md

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+20
LICENSE

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説明文

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+10
人気

GitHub Stars 100以上

0/15
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1ヶ月以内に更新

+10
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+5
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オープンIssueが50未満

+5
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プログラミング言語が設定されている

+5
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1つ以上のタグが設定されている

+5

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