policy-research-design

policy-research-design is a skill for Claude Code from parkjui92/policy-research-kit. It costs 152 tokens per session (1,845 once invoked), scanned A, original, MIT.

A planning method for starting policy research by clarifying its purpose, scope, research questions, analysis framework, report structure, and methods. Policy research examines public problems and possible government actions.

In plain words
What is it for?
Use it when beginning a policy study or analysis. It helps turn a broad topic into answerable questions, choose a suitable way to compare or assess options, and outline the report.
Why use it?
An unclear question or oversized scope can make an entire report unusable. Early design exposes missing decisions before detailed research and writing begin.

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 when beginning a policy study or analysis. It helps turn a broad topic into answerable questions, choose a suitable way to compare or assess options, and outline the report.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/parkjui92/policy-research-kit/policy-research-design
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-design
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-design

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/parkjui92/policy-research-kit/policy-research-design"><img src="https://agentmods.dev/badge/skills/parkjui92/policy-research-kit/policy-research-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 152 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,845 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 $0.00152 $0.01845
Opus 5 $0.00076 $0.00923
Sonnet 5 $0.00030 $0.00369
Haiku 4.5 $0.00015 $0.00185

Measured 11d ago against content hash b068e08f0090, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

policy-research-design 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.

skills/policy-research-design/SKILL.md · 86 lines

How it starts

The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.

정책연구 설계

정책연구의 방향을 착수 시점에 확정한다. 잘못된 RQ·목차로 보고서를 다 쓰고 갈아엎는 비용을 설계 단계에서 제거하는 것이 목적이다. 산출물은 _workspace/01_research_design.md.

Phase 0 — 의도분석 (먼저 한다)

본격 설계 전에 요청을 분해한다. 추측으로 넘어가지 않는다.

분류 체크리스트:

  • 목적 — 이 연구가 답해야 할 정책적 질문/의사결정은 무엇인가? (현황 진단? 대안 비교? 효과 평가? 제도 설계?)
  • 대상·범위 — 정책 대상(인구·지역·산업), 시간 범위, 비교군이 명확한가?
  • 산출물 — 최종 형태(보고서 분량·수준), 독자(결정자·실무·일반)는?
  • 숨은 가정 — 사용자가 당연시하는 전제(특정 대안 선호, 결론 방향)가 있는가? 있다면 드러낸다.
  • scope creep — 한 보고서에 담기 과한 범위인가? 핵심만 남기고 덜어낼 것을 찾는다.

모호한 항목은 사용자 확인 질문 3~5개로 만든다. 이 질문이 설계 산출물의 최상단에 온다.

RQ(연구질문) 도출

막연한 주제를 답할 수 있는 1~3개의 핵심 질문으로 좁힌다.

  • 좋은 RQ: 구체적·검증 가능·정책적 함의 있음. 예: "청년 1인가구의 주거비 부담은 어느 계층에서 가장 심각하며, 어떤 정책수단이 가장 비용효과적인가?"
  • 나쁜 RQ: "청년 주거 문제에 대해 알아본다" (질문이 아니라 주제)
  • RQ가 2개 이상이면 우선순위를 매긴다.

분석틀 선택

RQ에 답하기 위한 사고의 골격을 고른다. 왜 이 틀인지 한 줄 근거를 붙인다.

분석틀 적합한 상황
현황→원인→쟁점→대안→제언 일반 정책연구 기본형
정책수단 비교(효과·비용·실현성·수용성) 대안 선택이 핵심일 때
이해관계자 분석 갈등·조정이 핵심일 때
논리모형(투입-활동-산출-성과) 사업·프로그램 평가
PEST / SWOT 환경 진단이 필요할 때
국내외 비교사례 분석 벤치마킹이 핵심일 때

복수 틀을 조합해도 된다. 다만 보고서 전체를 관통하는 주(主) 틀은 하나로.

목차·연구방법 설계

표준 목차(기본 골격) — RQ에 맞게 구체화하되 아래 학술·정책연구 표준 구조를 기본으로 한다:

  1. 서론 — 배경·목적·연구질문(RQ)·범위·방법
  2. 이론적 배경 — 개념의 조작적 정의, 분석틀, 선행연구 검토(기존 논의와 공백)
  3. 해외 동향 분석 — 주요국·국제기구 정책 동향·사례(성공·실패)
  4. 국내 현황 분석 — 통계·실태로 본 국내 현황 진단(분석틀 적용, 분야별 매트릭스 등)
  5. 정책 대안 — 대안 도출·비교(효과·실현성·비용·수용성)·권고
  6. 정책 우선순위·추진 로드맵 — 우선순위, 단계·재원·거버넌스
  7. 정책제언 및 결론 — 실행 제언(5요소), 한계, 후속과제
  8. 참고문헌 — 본문 인용 출처 일괄 정리

각 장·절에 연구방법과 필요근거를 붙인다 — 조사관이 바로 착수할 수 있도록. 진단의 분석 장치(분야 매트릭스·2단 선별·4축 등)는 위 표준 목차의 4·5장에 배치한다.

분량 설계: 별도 지정이 없으면 본문 최소 50p를 기본 목표로, 장별 분량을 배분한다(예: 2장 이론 8p, 3장 해외 10p, 4장 국내 14p, 5장 대안 12p 등). 분량은 근거·분석의 깊이로 채울 수 있게 각 절의 필요근거 수를 충분히 잡는다.

목차 사용자 승인: 이 목차는 설계 게이트 통과 후 사용자 검토·승인을 받는다(오케스트레이터가 제시). 사용자가 바로 검토할 수 있도록 목차를 명료하고 한눈에 보이게 정리하라.

브리프 모드 설계 (단형 4~8p): 오케스트레이터가 "브리프 모드"를 지정하면 위 8장 표준 목차 대신 압축 목차(① 배경·문제제기 → ② 핵심 현황·쟁점 → ③ 핵심 근거 → ④ 정책제언 우선순위)를 설계한다. RQ는 1개로 좁히고, 분석틀은 "핵심 쟁점 → 제언"의 최소 골격으로, 장별 분량은 1~2p씩 배분한다. 설계 산출물도 가볍게(의도분석·RQ·압축목차·필요근거 핵심만) 쓴다. 핵심은 "무엇을 버리고 무엇 한 가지를 말할 것인가"다.

Read the full file on GitHub · 86 lines

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. 11d ago First seen · 86 lines · 152 tokens per session scan A b068e08f0090

Subscribe to this mod's changes

policy-research-design is a skill published in the GitHub repository parkjui92/policy-research-kit (9 stars, last pushed 1mo ago), licensed MIT. It adds 152 tokens to every session and 1,845 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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