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 skills add Insajin/autopus-adk --skill double-diamondgit clone --depth 1 https://github.com/Insajin/autopus-adkWrote 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/insajin/autopus-adk/double-diamond)<a href="https://agentmods.dev/skills/insajin/autopus-adk/double-diamond"><img src="https://agentmods.dev/badge/skills/insajin/autopus-adk/double-diamond/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.
<a href="https://agentmods.dev/skills/insajin/autopus-adk/double-diamond"><img src="https://agentmods.dev/badge/skills/insajin/autopus-adk/double-diamond.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00017 | $0.00549 |
| Opus 5 | $0.00009 | $0.00275 |
| Sonnet 5 | $0.00003 | $0.00110 |
| Haiku 4.5 | $0.00002 | $0.00055 |
Grade A, and why
double-diamond 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.
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
Double Diamond Skill
문제를 발산적으로 탐색하고 수렴하는 4단계 디자인 방법론입니다.
다이아몬드 1: 올바른 문제 찾기
Discover 단계 (발산)
문제 공간을 넓게 탐색합니다:
- 현장 조사: 실제 사용자 관찰
- 인터뷰: 이해관계자 심층 인터뷰
- 데이터 분석: 기존 로그와 메트릭 분석
- 경쟁 분석: 유사 솔루션 조사
목표: 가능한 한 많은 인사이트 수집
방법: 가정하지 말고 관찰하라
Define 단계 (수렴)
수집한 인사이트에서 핵심 문제를 정의합니다:
- 어피니티 다이어그램: 패턴 그룹화
- How Might We: 문제를 기회로 재정의
- Problem Statement: 한 문장으로 문제 정의
Problem Statement 형식:
[사용자]는 [맥락]에서 [목표]를 달성하려 하지만 [장애물] 때문에 어렵다.
다이아몬드 2: 올바른 해결책 개발
Develop 단계 (발산)
다양한 해결책을 탐색합니다:
- Crazy 8s: 빠른 아이디어 스케치
- 프로토타입: 저충실도 프로토타입
- 사용자 테스트: 빠른 검증
- 반복: 학습 기반 개선
Deliver 단계 (수렴)
최종 해결책을 선택하고 구현합니다:
- 평가 기준 설정: 무엇으로 성공을 측정할 것인가?
- 최종 선택: 최적 솔루션 결정
- 구현 계획: 단계별 실행 계획
- 측정 방법: KPI 설정
적용 체크리스트
- Discover: 최소 5가지 인사이트 수집
- Define: 명확한 Problem Statement 작성
- Develop: 최소 3가지 해결책 탐색
- Deliver: 검증 가능한 성공 지표 정의
전환 판단 기준
| 단계 | → 다음 단계 조건 |
|---|---|
| Discover → Define | 충분한 인사이트 수집 완료 |
| Define → Develop | 핵심 문제 합의 완료 |
| Develop → Deliver | 솔루션 검증 완료 |
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.
- 10d ago First seen · 70 lines · 17 tokens per session scan A 96c4ad8481c9
double-diamond is a skill published in the GitHub repository Insajin/autopus-adk (111 stars, last pushed yesterday), licensed MIT. It adds 17 tokens to every session and 549 once invoked, about $0.0001 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 2026-08-30.
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