paper-analysis

paper-analysis is a skill for Claude Code from parkjui92/socsci-paper-kit. It costs 154 tokens per session (1,123 once invoked), scanned A, original, MIT.

A data-analysis skill for social-science research using numerical data, interview or text data, or both. It checks data quality before testing hypotheses and reports results with tables, figures, and limitations.

In plain words
What is it for?
Running descriptive statistics, group comparisons, regression, factor analysis, qualitative coding, thematic analysis, and mixed-methods analysis.
Why use it?
It helps prevent conclusions from exceeding what the data supports and makes the analysis choices explicit.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the socsci-paper-kit plugin — 7 skills, 6 agents shipped together

Good fit Running descriptive statistics, group comparisons, regression, factor analysis, qualitative coding, thematic analysis…

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/parkjui92/socsci-paper-kit/paper-analysis
Install

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.

Any agent
npx skills add parkjui92/socsci-paper-kit --skill paper-analysis
Clone the repo
git clone --depth 1 https://github.com/parkjui92/socsci-paper-kit

Made for: Claude Code.

Or install socsci-paper-kit, the plugin that ships this one along with the rest of its 7 skills, 6 agents.

Wrote 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.

agentmods badge for paper-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/parkjui92/socsci-paper-kit/paper-analysis.svg)](https://agentmods.dev/skills/parkjui92/socsci-paper-kit/paper-analysis)
Your own site
<a href="https://agentmods.dev/skills/parkjui92/socsci-paper-kit/paper-analysis"><img src="https://agentmods.dev/badge/skills/parkjui92/socsci-paper-kit/paper-analysis.svg" alt="Measured on agentmods" height="20"></a>
Per session 154 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,123 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00154 $0.01123
Opus 5 $0.00077 $0.00562
Sonnet 5 $0.00031 $0.00225
Haiku 4.5 $0.00015 $0.00112

Measured 6d ago against content hash ebaf8ae32e59, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

paper-analysis 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 6d 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.

skills/paper-analysis/SKILL.md · 65 lines

What it actually says

사회과학 데이터 분석

가설을 데이터에 비추어 검증하고 결과를 정직하게 보고한다. 산출물은 _workspace/03b_data_analysis.md. 핵심 원칙은 데이터가 지지하는 범위 안에서만 말한다.

0. 데이터 무결성 점검 (분석 전 먼저)

  • 구조 — 표본 크기, 변수 수, 측정 수준(명목/서열/등간/비율).
  • 결측·이상치 — 결측 패턴·비율, 이상치 탐지와 처리 방침(명시).
  • 분포 — 정규성·왜도·첨도(양적 분석 전제 점검용).
  • 신뢰도·타당도 — 척도 신뢰도(Cronbach's α 등), 구성타당도. 문제는 분석 전에 드러낸다.

양적 분석

  1. 기술통계 — 평균·표준편차·빈도, 변수 분포 요약.
  2. 추론통계(가설별 기법 선택):
RQ/가설 성격 변수 기법
두 집단 차이 연속 종속 t-검정
세 집단+ 차이 연속 종속 ANOVA
범주 간 연관 범주형 카이제곱
변수 간 관계 연속 상관분석
예측·인과 연속/이항 종속 회귀(선형/로지스틱)
잠재구조 다항목 척도 요인분석·SEM
  1. 보고 — 검정통계량·자유도·p값·효과크기를 함께 제시한다. 전제가정(정규성·등분산·독립성 등)을 점검하고, 위배 시 비모수 대안이나 보정을 적용·명시한다.
  2. 금지 — 원하는 결과가 나올 때까지 분석을 바꾸거나(p-hacking), 유의한 결과만 선택 보고하지 않는다.

질적 분석

  1. 코딩 — 개방코딩 → 축코딩 → 선택코딩. 코드북을 정리한다.
  2. 주제분석 — 코드를 범주·주제로 묶고, 대표 인용(원자료 발췌)으로 뒷받침한다.
  3. 엄밀성 — 코더 간 일치도, 삼각검증(자료·연구자·이론), 포화 도달 여부, 부정 사례(negative case) 검토를 보고한다.

혼합 분석

양적·질적 결과를 RQ를 중심으로 통합한다 — 수렴(두 결과가 일치하는가), 보완(서로 다른 측면을 채우는가), 확장(한쪽이 다른쪽을 설명하는가). 통합 표(joint display)를 활용한다.

결과 표현

  • 표·그림 — 번호·제목·출처/주를 갖춘다. 본문에서 반드시 언급·해석된다.
  • 해석 범위 — 상관을 인과로, 표본을 모집단으로 비약하지 않는다. 통계적 유의성과 실질적 중요성을 구분한다.

한계 기술

표본·측정·설계·분석의 한계를 정직하게 적는다. 결과의 일반화 가능 범위를 명시한다.

출력 구조 (03b_data_analysis.md)

  1. 데이터·무결성 점검 (표본·결측·신뢰도)
  2. 분석 절차 (사용 변수·기법·도구/코드)
  3. 결과 (표·그림 + 수치)
  4. 가설 지지여부 (가설별 지지/기각 + 근거)
  5. 해석
  6. 가정·한계

주의

  • 데이터를 위조·임의 생성하지 않는다. 수치가 필요하나 데이터가 없으면 "[데이터 필요]"로 남긴다(READ-ONLY 무결성).
  • 분석 절차를 재현 가능하게 기록한다.
  • 데이터 없는 이론·문헌 연구에는 이 단계가 적용되지 않는다(오케스트레이터가 건너뜀).
Changes

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.

  1. 6d ago First seen · 65 lines · 154 tokens per session scan A ebaf8ae32e59

Subscribe to this mod's changes

paper-analysis is a skill published in the GitHub repository parkjui92/socsci-paper-kit (4 stars, last pushed 28d ago), licensed MIT. It adds 154 tokens to every session and 1,123 once invoked, about $0.0008 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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