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 skills/kyopark2014/agent-plugins/account-statusnpx skills add kyopark2014/agent-plugins --skill account-statusgit clone --depth 1 https://github.com/kyopark2014/agent-pluginsWrote 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/skills/kyopark2014/agent-plugins/account-status)<a href="https://agentmods.dev/skills/kyopark2014/agent-plugins/account-status"><img src="https://agentmods.dev/badge/skills/kyopark2014/agent-plugins/account-status.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 | $0.00059 | $0.03329 |
| Opus 5 | $0.00030 | $0.01665 |
| Sonnet 5 | $0.00012 | $0.00666 |
| Haiku 4.5 | $0.00006 | $0.00333 |
Grade A, and why
account-status 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.
How it starts
The opening of the file, as written. The whole thing — 247 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Account Status (Single Account)
이 스킬은 계정명 하나를 입력받아 해당 계정의 지출/매출 상태를 분석하고, HTML 리포트를 생성한 뒤 차트를 이미지(JPEG 권장)로 변환하여 이메일 본문에 포함해 발송합니다.
Language (필수)
- 사용자에게 보이는 분석 문장, 요약, 권장 조치, 이메일 본문은 한국어로 작성합니다.
- API 필드명/코드 식별자는 원문 그대로 사용해도 되지만, 해설은 한국어로 유지합니다.
Purpose
- SFDC의 정보를 기반으로 계정 분석을 수행합니다.
- 입력값은 account name이며, 이름으로 계정을 찾은 후 1개 계정을 대상으로 리포트를 만듭니다.
- 이메일 클라이언트 JS 미실행 제약 때문에 Chart.js 결과를 이미지로 변환해 포함합니다.
When to Use This Skill
- 특정 한 개 계정의 최신 상태를 빠르게 보고하고 싶을 때
- 계정별 매출/지출 변화, AWS 계정 매핑 상위 기여도를 이메일로 공유해야 할 때
- 기존 2개 계정 동시 리포트가 너무 커서 메일 방송이 어려운 경우
Workflow
Step 1) Resolve target account from account name
사용자에게 계정명을 받습니다. 이름으로 계정을 조회해 정확히 1개 대상 계정을 확정합니다.
-
아래 두 계정은 알려진 SFDC Account ID로 우선 매핑할 수 있습니다:
LG Chemical→0015000000fSYKUAA4LG Energy Solution(LG Ensol) →0014z00001bw6vaAAASK E&S→0013800001FFCZ7AAPSK Chemicals→0013800001G2bXHAAZSK Gas→0013800001DG1Y6AALSK Innovation→0013800001FFCZ2AAPSK Discovery→0010z00001TgcUHAAZSK D&D→0010z00001XDeFaAALLX Semicon→0013800001CCbE4AALSeoul Semiconductor→0013800001MGKpLAAX
-
입력 계정명이 위 별칭과 일치/유사하면 조회 전에 해당 ID를 우선 사용해도 됩니다.
-
동명이인이 여러 개면 사용자에게 후보를 보여주고 선택을 받습니다.
-
계정이 없으면 실패 사유를 알리고 종료합니다.
조회 결과에서 최소한 아래 값을 확보합니다:
accountId(SFDC account id)accountName
확정 후 조회 예시:
get_account_spend_summary(sfdcAccountId: "<resolved_account_id>")
get_account_spend_history(accountId: "<resolved_account_id>", includeMonthlyBreakdown: true)
Step 2) Fetch financial and mapping data
확정된 단일 계정에 대해 아래 데이터를 조회합니다.
- spend summary
- spend history (월별 포함)
- AWS account mappings (
chargeR12기준 정렬, 충분한 limit) - 서비스별 지출 데이터(서비스명 + R12 금액이 포함된 breakdown; 가능 시
chargeR12기준 정렬)
가능하면 병렬 호출합니다.
AWS account 매핑 분석은 MoM(전월 대비) 중심으로 제공합니다.
aws_sentral에서 제공되는momPercentCharge를 기준으로 증감 추이를 해석합니다.- AWS account 단위 YoY는 계산/신뢰 가능한 방식으로 제공하지 않으므로 분석 항목에서 제외합니다.
Step 3) Compute metrics
What ships with it
4 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.
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 · 247 lines · 59 tokens per session scan A a65f8849108c
account-status is a skill published in the GitHub repository kyopark2014/agent-plugins (4 stars, last pushed today), licensed MIT. It adds 59 tokens to every session and 3,329 once invoked, about $0.0003 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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