Borrowing it
Nothing to install: this file belongs to tobyilee/book-writer. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/tobyilee/book-writer/main/.claude/skills/paper-research/SKILL.mdgit clone --depth 1 https://github.com/tobyilee/book-writerWrote 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.
[](https://agentmods.dev/skills/tobyilee/book-writer/paper-research)<a href="https://agentmods.dev/skills/tobyilee/book-writer/paper-research"><img src="https://agentmods.dev/badge/skills/tobyilee/book-writer/paper-research/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.
<a href="https://agentmods.dev/skills/tobyilee/book-writer/paper-research"><img src="https://agentmods.dev/badge/skills/tobyilee/book-writer/paper-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00080 | $0.00664 |
| Opus 5 | $0.00040 | $0.00332 |
| Sonnet 5 | $0.00016 | $0.00133 |
| Haiku 4.5 | $0.00008 | $0.00066 |
Grade A, and why
paper-research 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 9d ago.
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.
What it actually says
Paper Research
학술 자료에서 이론·방법·실증 결과를 수집한다. 대중 자료나 커뮤니티 토론은 다루지 않는다.
절차
- 검색 전략 수립
- 서베이 논문을 먼저 찾는다 (분야 전체 조감에 유리)
- 그 다음 seminal 논문 (피인용 500+) 2~3편
- 그 다음 최근 3년 내 주요 논문 3~5편
- 검색 소스
- arXiv (사전 인쇄)
- Google Scholar (피인용 순)
- Semantic Scholar API (abstract·링크 조회 유리)
- 분야별 학회·저널 (ACM, IEEE, ACL 등)
- 논문 평가
- 피인용수, 발표처, 재현성 여부 확인
- 추출 — 각 논문에서:
- 핵심 주장 (3~5문장)
- 방법론 요약 (대상 독자 수준에 맞게 추상화)
- 수치·실험 결과
- 인용 가능한 문장 (원문 페이지·섹션 표시)
- 저장 —
{slug}/research/papers.md
가이드
- 목표 건수: 3~10편
- 최신성·고전 균형: 7:3 또는 5:5
- 독자 수준 고려: 비학문 개발자 대상이면 수학적 증명은 축약, 결과와 직관 중심
- 재현성 점검: 코드·데이터 공개 여부를 체크해 "실제로 써볼 수 있는" 자료 우선
출력 형식
# 논문 리서치: {주제}
## 논문 1: {제목}
- 저자·연도: {...}
- 발표처: {학회·저널명, 볼륨}
- DOI/arXiv ID: {...}
- 피인용수: {숫자, 조회 시점}
- 요약 (3~5문장):
- 방법론 요약:
- 핵심 수치·결과:
- 인용할 만한 문장:
> "..." (p.{페이지})
- 독자 전달 방식 제안: {비유·단순화 아이디어}
실패 대응
- arXiv·Scholar 접근 실패 → Semantic Scholar API 활용
- 논문 전문 접근 불가 → abstract + 공개 프리프린트 기반, 한계 명시
- 서베이 논문 없음 → 분야 리뷰 아티클(예: ACM Computing Surveys)로 대체
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.
- 9d ago First seen · 60 lines · 80 tokens per session scan A 1d66ec7e331d
paper-research is a skill published in the GitHub repository tobyilee/book-writer (81 stars, last pushed 23d ago), licensed MIT. It adds 80 tokens to every session and 664 once invoked, about $0.0004 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.
Other skills, from other repositories
instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…
exploratory-data-analysis
Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…
matlab
Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
phylogenetics
Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
mapping-to-snomed
Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…