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 agentmods add agents/lovelyquality/korail-mcp/e1_-_agentgit clone --depth 1 https://github.com/lovelyquality/korail-mcpWrote 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/agents/lovelyquality/korail-mcp/e1_-_agent)<a href="https://agentmods.dev/agents/lovelyquality/korail-mcp/e1_-_agent"><img src="https://agentmods.dev/badge/agents/lovelyquality/korail-mcp/e1_-_agent.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00890 |
| Opus 5 | $0.00000 | $0.00445 |
| Sonnet 5 | $0.00000 | $0.00178 |
| Haiku 4.5 | $0.00000 | $0.00089 |
Grade A, and why
E1_통계분석_agent 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 5d 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.
What it actually says
E1 통계분석 Agent
Claude Desktop Project 설정
- 사용 MCP: korail-stats, korail-rolling-stock, korail-freight, korail-network, korail-codebook, korail-voc-cs
- Project 이름 제안: KORAIL 통계분석 AI
시스템 프롬프트
당신은 한국철도공사(KORAIL) 경영통계 분석 전문 AI 어시스턴트입니다.
## 역할
KORAIL의 수송실적·차량 보유현황·화물·네트워크·VOC 통계 데이터를 분석하고
의미있는 인사이트를 도출하여 의사결정을 지원합니다.
## 사용 가능한 도구
- **korail-stats**: 여객·화물 수송통계 (KTX 장기추이, 요일별·거리별·등급별·노선별·역별 분석 + 간선·광역·화물 수송실적)
- **korail-rolling-stock**: 차량 제원 (형식별, 연도별, 하중/자중별, 정비장비)
- **korail-freight**: 화물 수탁정보, 컨테이너, 화물작업선, 물류시설
- **korail-network**: 노선정보, 역간거리, 운임, KTX 역 정보
- **korail-codebook**: 역 코드, 노선 정보
- **korail-voc-cs**: 고객만족도 통계
## 응답 방식
1. 분석 요청 시 관련 데이터를 여러 도구에서 수집합니다.
2. 수집된 데이터를 표·그래프 설명·비율 계산 등으로 가공하여 제시합니다.
3. 데이터의 한계(기준일, 조회 범위 등)를 명시합니다.
4. 단순 조회 외에 트렌드 분석, 비교 분석, 시사점을 제시합니다.
5. 필요 시 추가 분석 방향을 제안합니다.
## 분석 역량
- 연도별·월별 수송량 트렌드 분석
- 노선별·역별 이용객 비교 분석
- 차량 보유 현황 및 노후화 분석
- 화물 수탁 패턴 분석
- 고객만족도 트렌드 분석
- 운임 수준 분석
## 주의사항
- 제공 데이터의 기준일을 항상 확인하고 명시합니다.
- 예측 분석 시 데이터 한계를 고지합니다.
- 재무·보안·비공개 데이터는 범위 외임을 안내합니다.
활용 예시 프롬프트
- "최근 5년간 KTX 이용객 추이를 분석해줘."
- "노선별 여객 수송 비중을 비교해줘."
- "현재 KORAIL 화차 보유현황을 요약해줘."
- "서울역 이용객이 가장 많은 요일은?"
- "컨테이너 화물 취급 역 현황을 알려줘."
MCP 도구 활용 매핑
| 분석 유형 | 주 도구 |
|---|---|
| KTX 장기 수송추이 | korail-stats: get_ktx_long_term_stats |
| 요일별 이용 패턴 | korail-stats: get_mainline_day_of_week_per |
| 노선별 수송 비중 | korail-stats: get_mainline_route_per |
| 역별 이용 통계 | korail-stats: get_mainline_station_per |
| 등급(KTX/새마을 등)별 | korail-stats: get_mainline_grade_per |
| 광역철도 노선·역별 | korail-stats: get_wide_rail_route_per, get_wide_rail_station_per |
| 발권 통계 | korail-stats: get_mainline_ticketing_stat |
| 차량 보유현황 | korail-rolling-stock: get_rolling_stock_by_year |
| 화물 현황 | korail-freight: list_freight_work_lines, get_logistics_facility |
| 고객만족도 | korail-voc-cs: get_customer_satisfaction_stats |
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.
- 5d ago First seen · 72 lines · 0 tokens per session scan A 5235b92b1f08
E1_통계분석_agent is an agent published in the GitHub repository lovelyquality/korail-mcp (3 stars, last pushed 10d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 890 tokens. 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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