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.
npx skills add parkjui92/socsci-paper-kit --skill socsci-paper-orchestratorgit clone --depth 1 https://github.com/parkjui92/socsci-paper-kitWrote 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/parkjui92/socsci-paper-kit/socsci-paper-orchestrator)<a href="https://agentmods.dev/skills/parkjui92/socsci-paper-kit/socsci-paper-orchestrator"><img src="https://agentmods.dev/badge/skills/parkjui92/socsci-paper-kit/socsci-paper-orchestrator/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/parkjui92/socsci-paper-kit/socsci-paper-orchestrator"><img src="https://agentmods.dev/badge/skills/parkjui92/socsci-paper-kit/socsci-paper-orchestrator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00384 | $0.05078 |
| Opus 5 | $0.00192 | $0.02539 |
| Sonnet 5 | $0.00077 | $0.01016 |
| Haiku 4.5 | $0.00038 | $0.00508 |
Grade A, and why
socsci-paper-orchestrator 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
사회과학 논문 오케스트레이터
실제 사회과학 연구를 6인 에이전트 팀으로 수행해 학술논문(.docx + .md)을 산출한다. OmO(oh-my-openagent)의 핵심 패턴인 2단계 검증 게이트(집필 전 설계 검토 + 집필 후 5축 검수)를 이식했다.
실행 모드: 에이전트 팀
에이전트 구성
| 팀원 | 타입 | 역할 | 스킬 | 출력 |
|---|---|---|---|---|
| paper-designer | paper-designer | 의도분석 + RQ·가설·이론틀·연구방법·목차 설계 | paper-design | 01_research_design.md |
| paper-reviewer | paper-reviewer | (모드1) 설계 게이트 / (모드2) 5축 초안 검수 | paper-review | 02_design_review.md, 05_draft_review.md |
| paper-investigator | paper-investigator | 선행연구(SLR)·이론출처·통계·사례 조사, 출처 병기 | paper-research | 03_literature.md |
| paper-analyst | paper-analyst | 데이터분석 — 양적·질적·혼합 (조건부) | paper-analysis | 03b_data_analysis.md |
| paper-writer | paper-writer | 본문 집필 (서론→이론→방법→결과→논의→결론) + 참고문헌 | paper-writing | 04_paper_draft.md |
| paper-finalizer | paper-finalizer | 한국어 교정교열 + docx/md 변환 | paper-proofread + docx | 06_paper.docx, 06_paper.md |
모든 팀원은 기본적으로 세션 모델을 상속해 스폰한다(품질 우선 시 model: "opus" — 공개판 실행 노트 참조). 검토관(reviewer)은 파이프라인에서 두 번 등판한다(설계 후·초안 후). paper-analyst는 조건부 — 실증연구(양적/질적/혼합)면 투입, 데이터 없는 이론·문헌 연구면 이 단계를 건너뛴다.
워크플로우
Phase 0: 컨텍스트 확인 (후속 작업 지원)
작업 디렉토리의 _workspace/ 존재 여부로 실행 모드를 결정한다:
_workspace/미존재 → 초기 실행. Phase 1로._workspace/존재 + 부분 수정 요청 (예: "설계 다시", "논의 장만 다시", "데이터 재분석", "근거 보강", "검수 다시", "docx만 재생성") → 부분 재실행. 해당 에이전트만 재호출하고 그 산출물만 갱신한다. 의존 산출물(설계 변경 시 → 조사·분석·집필·검수도 영향)을 함께 갱신할지 판단한다._workspace/존재 + 새 주제/새 입력 → 새 실행. 기존_workspace/를_workspace_{YYYYMMDD_HHMMSS}/로 이동 후 Phase 1로.
부분 재실행 시 이전 산출물 경로를 해당 에이전트 프롬프트에 포함해, 기존 결과를 읽고 피드백을 반영하도록 지시한다.
Phase 1: 준비 (입력 수집 + 자료 라우팅 + 연구유형 판별)
- 사용자 입력 분석 — 연구 주제, RQ 단서, 메모, 기존 초안·선행연구·데이터셋·통계, 방법론(양적/질적/혼합/이론), 목표 산출물(학위논문/저널·분량), 출력 경로, 인용형식(기본 APA7)을 파악한다.
_workspace/생성 (새 실행이면 기존 것을 타임스탬프 디렉토리로 이동 후 재생성).- 입력 자료 저장 + 인덱싱 — 사용자가 준 모든 자료를
_workspace/00_input/에 저장하고,_workspace/00_input/_index.md에 "파일명 — 성격(초안/데이터/선행연구/메모) — 어느 단계·에이전트가 쓸지"를 한 줄씩 기록한다. 이 인덱스가 라우팅의 핵심이다.- 자료 라우팅 규칙: 주제·범위 단서 → designer / 선행연구·이론출처·통계 → investigator / 데이터셋 → analyst / 기존 초안 → writer(베이스로 개정) + reviewer(검수 대상) / 인용형식·템플릿 → finalizer.
- 기존 초안 제공 시: 백지 집필이 아니라 그 초안을 출발점으로 삼는다. designer는 초안 구조를 분석해 RQ·가설·목차를 역설계·보완하고, investigator는 초안 주장의 출처를 검증·보강하며, writer는 초안을 개정한다. 이 분기를 각 에이전트 프롬프트에 명시한다.
- 연구유형 판별(잠정) — 데이터 유무·방법론으로 paper-analyst 투입 여부를 잠정 결정한다(최종 확정은 Phase 3 설계에서). 이론·문헌 연구면 분석 단계를 건너뛸 계획을 세운다.
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.
- 11d ago First seen · 170 lines · 384 tokens per session scan A 25c04c19cae2
socsci-paper-orchestrator is a skill published in the GitHub repository parkjui92/socsci-paper-kit (4 stars, last pushed 1mo ago), licensed MIT. It adds 384 tokens to every session and 5,078 once invoked, about $0.0019 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 2026-08-31.
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