public-sector-research

public-sector-research is a skill for Codex from Kminer2053/public-sector-research-skill. It costs 86 tokens per session (1,304 once invoked), scanned A, original, MIT.

An evidence-first research workflow for questions about governments, laws, public services, policy, procurement, or privacy. It collects official sources, records supporting passages, and produces readable Korean Markdown and interactive HTML reports.

In plain words
What is it for?
Use it to plan and run public-sector investigations, collect official documents, track citations, identify gaps, and build reviewable reports.
Why use it?
It makes research easier to check by preserving the sources, evidence, limits, and scoring behind a conclusion. Local SQLite storage lets the project retain research information for later use.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions Codex.

Good fit Use it to plan and run public-sector investigations, collect official documents, track citations, identify gaps, and build reviewable reports.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kminer2053/public-sector-research-skill/public-sector-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 Kminer2053/public-sector-research-skill --skill public-sector-research
Clone the repo
git clone --depth 1 https://github.com/Kminer2053/public-sector-research-skill

Made for: Codex.

Its marketplace also offers this one on its own, as the plugin public-sector-research/plugin install public-sector-research after adding the marketplace above.

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 public-sector-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/kminer2053/public-sector-research-skill/public-sector-research/github.svg)](https://agentmods.dev/skills/kminer2053/public-sector-research-skill/public-sector-research)
Your own site
<a href="https://agentmods.dev/skills/kminer2053/public-sector-research-skill/public-sector-research"><img src="https://agentmods.dev/badge/skills/kminer2053/public-sector-research-skill/public-sector-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 public-sector-research

Your own site · 80×15
<a href="https://agentmods.dev/skills/kminer2053/public-sector-research-skill/public-sector-research"><img src="https://agentmods.dev/badge/skills/kminer2053/public-sector-research-skill/public-sector-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,304 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 $0.00086 $0.01304
Opus 5 $0.00043 $0.00652
Sonnet 5 $0.00017 $0.00261
Haiku 4.5 $0.00009 $0.00130

Measured 12d ago against content hash fbf022a450ac, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

public-sector-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 12d ago.

The scan reads SKILL.md. This mod also ships 13 executable files (scripts/psr_core/__init__.py, scripts/psr_core/briefing.py, scripts/psr_core/cli.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/public-sector-research/SKILL.md · 88 lines

How it starts

The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.

공공복리 · BOKRI

공공복리(복리)는 공공업무 질문을 바로 요약하지 않고, 공식 원문을 확보한 뒤 근거 구간과 한계를 검토 가능한 형태로 남긴다. 이 Skill은 특정 AI 서비스의 검색 기능에 종속되지 않는다. 호스트가 제공하는 웹 검색·브라우저·커넥터로 공식 출처를 찾고, bundled Python CLI로 계획·수집·저장·점수화·보고서 생성을 수행한다.

실행 진입점

Skill 폴더의 scripts/psr.py를 사용한다.

python3 <skill-directory>/scripts/psr.py --version

설치형 CLI가 있으면 같은 계약의 psr 명령을 사용해도 된다.

기본 워크플로

  1. 사용자의 업무 목적, 기준일, 관할, 산출물을 확인한다.
  2. 프로젝트에 .psr/가 없으면 로컬 저장소를 초기화한다.
  3. research plan을 실행하고 생성된 plan.json의 활성 track을 검토한다. 질문과 무관한 track은 --exclude-track, 반드시 필요한 track은 --include-track으로 조정한다.
  4. 각 track의 query와 preferred domain을 사용해 공식 원문을 우선 탐색한다.
  5. 선택한 출처를 JSONL manifest에 기록한다. 출처 등급을 추측하지 말고 확인 가능한 범위에서 지정한다.
  6. research run으로 출처를 병렬 수집·파싱하고 보수적인 초안 보고서를 생성한다.
  7. result.json의 citation을 검토한 뒤 reporting.md에 따라 brief.json을 작성한다.
  8. report build --brief-file <path> --format all로 Markdown과 HTML을 함께 생성한다.
  9. PARTIAL, gap, failure, 발행일 미확인, UNVERIFIED_WEB 항목을 먼저 검토한다.
  10. 사용자에게 핵심 내용과 함께 HTML·Markdown 경로, 핵심 citation ID, 공식 원문 미확보 범위를 알린다.

빠른 시작

python3 <skill-directory>/scripts/psr.py project init . --name "AI 구매원칙"

python3 <skill-directory>/scripts/psr.py --project . research plan \
  "공공기관 생성형 AI 구매 시 데이터 권리와 업체 종속 방지 원칙을 조사하라"

계획 출력의 run_id와 query를 사용해 출처를 찾은 뒤 sources.jsonl을 만든다.

{"track_id":"law-regulation","url":"https://official.example/law","title":"공식 법령","publisher":"공식기관","source_tier":"OFFICIAL_PRIMARY","published_at":"2026-01-01"}
{"track_id":"privacy","url":"https://official.example/privacy.pdf","title":"개인정보 안내서","publisher":"공식기관","source_tier":"OFFICIAL_PRIMARY","published_at":"2025-08-07"}
python3 <skill-directory>/scripts/psr.py --project . research run <run-id> \
  --sources-file sources.jsonl

재사용과 오프라인 작업

동일 출처의 최근 snapshot은 기본 7일 동안 재사용한다. 최신성 확인이 필요하면 --refresh를 사용한다.

python3 <skill-directory>/scripts/psr.py --project . memory search "학습 재사용"
python3 <skill-directory>/scripts/psr.py --project . evidence list --run-id <run-id>
python3 <skill-directory>/scripts/psr.py --project . report build <run-id> \
  --brief-file brief.json --format all

Read the full file on GitHub · 88 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. 12d ago First seen · 88 lines · 86 tokens per session scan A fbf022a450ac

Subscribe to this mod's changes

public-sector-research is a skill published in the GitHub repository Kminer2053/public-sector-research-skill (4 stars, last pushed 1mo ago), licensed MIT. It adds 86 tokens to every session and 1,304 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 2026-08-31.

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