policy-research

policy-research is a skill for Claude Code from parkjui92/policy-research-kit. It costs 141 tokens per session (1,362 once invoked), scanned A, original, MIT.

A research workflow for collecting sourced evidence for policy reports. It looks for official statistics, earlier studies, policy examples, laws, and institutional background.

In plain words
What is it for?
Use it to research a policy question, gather country-specific examples, compare existing studies, and prepare evidence with source details.
Why use it?
It reduces the work of finding reliable support for claims and helps distinguish documented facts from unsupported statements.

Skill for Claude Code

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

Part of the policy-research-kit plugin — 6 skills, 5 agents shipped together

Good fit Use it to research a policy question, gather country-specific examples, compare existing studies, and prepare evidence with source details.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/parkjui92/policy-research-kit/policy-research
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/policy-research-kit --skill policy-research
Clone the repo
git clone --depth 1 https://github.com/parkjui92/policy-research-kit

Made for: Claude Code.

Or install policy-research-kit, the plugin that ships this one along with the rest of its 6 skills, 5 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 policy-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/parkjui92/policy-research-kit/policy-research/github.svg)](https://agentmods.dev/skills/parkjui92/policy-research-kit/policy-research)
Your own site
<a href="https://agentmods.dev/skills/parkjui92/policy-research-kit/policy-research"><img src="https://agentmods.dev/badge/skills/parkjui92/policy-research-kit/policy-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.

agentmods 80×15 button for policy-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/parkjui92/policy-research-kit/policy-research"><img src="https://agentmods.dev/badge/skills/parkjui92/policy-research-kit/policy-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 141 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,362 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 $0.00141 $0.01362
Opus 5 $0.00071 $0.00681
Sonnet 5 $0.00028 $0.00272
Haiku 4.5 $0.00014 $0.00136

Measured 10d ago against content hash b98f24698ff1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

policy-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 10d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/geo_search.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/policy-research/SKILL.md · 61 lines

What it actually says

정책연구 근거조사

설계자의 RQ와 목차를 보고, 각 주장을 떠받칠 출처 있는 근거를 모은다. 정책보고서의 신뢰는 "출처가 있는 사실"에서 나온다. 산출물은 _workspace/03_evidence.md.

조사 대상 (목차 항목별로 채운다)

  1. 현황·실태 근거 — 문제의 규모·추이를 수치로. 정부 통계, 공식 지표, 실태조사.
  2. 선행연구·문헌 — 기존 정책연구·학술문헌의 논의와 공백(gap).
  3. 국내외 정책사례 — 유사 정책의 설계·효과·시사점. 해외는 OECD·EU·주요국 사례.
  4. 정책·제도 배경 — 관련 법령, 상위계획, 정책 연혁, 거버넌스.

해외 사례는 지역·언어 현지화

해외 정책사례·통계는 대상국 언어로 검색한다(일본=일본어, 독일=독일어…). 현지 로케일 검색이 필요하면 geo-search 래퍼: 이 스킬에 내장된 래퍼 python3 <이 스킬 디렉토리>/scripts/geo_search.py -c jp "日本語 検索語" (프리셋: us jp kr gb de fr cn tw sg, 임의 로케일 --gl/--hl). 기본 WebSearch는 US 고정이라 다른 나라 로케일엔 부적합. 키(SERPER_API_KEY/SERPAPI_KEY) 미설정 시 WebSearch 영문 쿼리로 폴백. 상세: 이 스킬의 scripts/geo-search-README.md.

출처 신뢰도 기준 (우선순위)

등급 출처 사용
1차(최우선) 통계청·KOSIS, 부처 공식자료, 국책연구기관(KDI·KIHASA·STEPI 등), OECD·World Bank, 법령(법제처) 핵심 수치·사실의 근거
2차 학술논문, 학회·협회 보고서, 국회입법조사처·예산정책처 해석·분석 근거
참고(주의) 언론·블로그 1차 출처로 가는 단서로만. 단독 근거 금지

블로그·언론에서 수치를 보면 그 수치의 원(原) 출처를 찾아 1차로 교체한다.

출처 표기 표준

모든 사실에 다음을 붙인다:

[사실/수치] (출처: 발행기관, 「문서명」, 발행연도, 페이지/표번호 또는 URL, 기준연도)
  • 수치는 기준연도·정의·단위·비교군을 함께 적는다. "실업률 7%"가 아니라 "청년(15~29세) 실업률 7.0%(통계청, 경제활동인구조사, 2024.12 기준)".
  • 추정·예측치는 "추정"임을 명시한다.
  • 참고문헌 대응: 각 출처는 말미 참고문헌으로 옮길 수 있게 완전한 서지정보(저자/기관·문서명·발행처·연도·페이지/표·URL·접근일)를 갖춰 기록한다. 작성가가 이 정보로 참고문헌을 만들고 검토관이 실재·일치를 검증하므로, 추후 검증 가능한 형태로 남긴다(접근 불가·원출처 불명은 그렇게 표기).

상충 자료 처리

자료 간 수치·해석이 다르면 삭제하지 않는다. 둘 다 출처와 함께 남기고 차이의 이유(기준연도·정의 차이 등)를 메모한다. 판단은 검토관·작성가에게 넘긴다.

출력 구조 (03_evidence.md)

목차 항목별로 묶는다:

## 3.1 주거비 부담 추이
- [사실] 청년 1인가구 RIR 28.5% (출처: 국토부, 주거실태조사, 2023, 표3-2)
  └ 메모: 전체 가구 평균(23.9%) 대비 4.6%p 높음. 추이는 2019년 26.1%→상승.
- [미확보] 2024년 잠정치 — 미공표. 추가 조사 필요.
  • 각 항목에 사실 + 출처 + 짧은 해석 메모.
  • 못 찾은 것은 **[미확보]**로 명시. 빈칸을 지어내지 않는다.

주의

  • 최신판 확인 — 정책·통계는 갱신이 잦다. 기준일을 명시한다.
  • 신뢰도 낮은 출처는 "참고(신뢰도 낮음)"로 구분 표기한다.
  • 조사만 한다(READ-ONLY). 본문 집필·파일 개정은 하지 않는다.
  • 작성가가 보강을 요청하면 해당 항목만 추가 조사해 덧붙인다(기존 출처 보존).
Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 10d ago First seen · 61 lines · 141 tokens per session scan A b98f24698ff1

Subscribe to this mod's changes

policy-research is a skill published in the GitHub repository parkjui92/policy-research-kit (9 stars, last pushed 1mo ago), licensed MIT. It adds 141 tokens to every session and 1,362 once invoked, about $0.0007 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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