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 auto-ideagit 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/auto-idea)<a href="https://agentmods.dev/skills/insajin/autopus-adk/auto-idea"><img src="https://agentmods.dev/badge/skills/insajin/autopus-adk/auto-idea/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/auto-idea"><img src="https://agentmods.dev/badge/skills/insajin/autopus-adk/auto-idea.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 | $0.00031 | $0.03904 |
| Opus 5 | $0.00015 | $0.01952 |
| Sonnet 5 | $0.00006 | $0.00781 |
| Haiku 4.5 | $0.00003 | $0.00390 |
Grade A, and why
auto-idea 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.
How it starts
The opening of the file, as written. The whole thing — 276 lines — stays where its author put it; the contents beside it link to each section on GitHub.
auto-idea — 아이디어 브레인스토밍 스킬
OMP Invocation
/auto idea .../auto-idea ...- Load detail skill
auto-ideafor either entrypoint.
프로젝트: autopus-adk | 모드: full
설명
멀티 프로바이더 오케스트라를 활용해 아이디어를 구조화하고 발산 후 BS 파일로 저장합니다.
ICE 스코어링으로 아이디어를 평가하고 상위 N개를 선별합니다.
Opportunity-Solution Tree, 다관점 브레인스토밍, 가정 식별을 포함합니다.
product-discovery, double-diamond, brainstorming 스킬의 문제 정의, 가정 검증, HMW/SCAMPER 흐름을 참고해 사용자의 의도를 먼저 구체화합니다.
Canonical Semantic Contract
{
"schema": "orchestration-contract.v1",
"workflow": "idea",
"semantics": {
"forward_strategy_and_providers": true,
"minimum_rounds": 2,
"fallback_minimum_rounds": 2,
"blind_separate_judge": true,
"fresh_judge_session": true,
"preserve_dissent": true
}
}
사용법
/auto-idea "아이디어 설명"
/auto-idea "아이디어 설명" --strategy consensus
/auto-idea "아이디어 설명" --auto
/auto-idea "아이디어 설명" --deep-clarify
플래그
| Flag | Description |
|---|---|
--strategy |
오케스트레이션 전략: debate (기본), consensus, pipeline, fastest |
--providers |
사용할 프로바이더 목록 (기본: 전체) |
--auto |
질문 없이 assumed/deferred rows 기록 후 /auto plan --from-idea BS-{ID} 자동 체이닝 |
--deep-clarify |
기본 1문항 대신 최대 3문항까지 clarification 허용 |
공통 플래그
--multi:idea에서는 기본적으로 orchestra가 기본 엔진이므로 사실상 항상 활성 상태로 취급합니다.--auto: 완료 후 plan 체이닝까지 자동 진행합니다.
OMP 기본 실행 모델
- OMP에서는
taskbatch 기반 subagent-first를 기본 원칙으로 사용합니다. idea에서는 메인 세션이 오케스트라 실행과 최종 합성을 담당합니다.- 관련 코드 탐색, 기존 패턴 조사, 리스크 정리처럼 병렬화 가능한 보조 작업은 서브에이전트로 위임합니다.
- 현재 OMP 런타임 정책이 암묵적
taskbatch 호출을 제한하면, 하네스 기본값과 제약을 명시적으로 알린 뒤 사용자에게 서브에이전트 진행 여부 또는 단일 세션 진행을 확인받습니다. - 아이디어 발산 자체를 불필요하게 잘게 쪼개지는 않습니다.
5단계 파이프라인
Step 1: 입력 파싱
입력에서 아이디어 설명과 플래그를 추출합니다.
Step 2: Intent Clarification Q&A + What/Why/Who/When 구조화
오케스트라를 호출하기 전에 사용자의 의도를 먼저 선명하게 만듭니다.
참고 스킬:
product-discovery: Outcome, Opportunity, Assumption, Experiment 구조double-diamond: Problem Statement와 Discover/Define 수렴brainstorming: HMW, SCAMPER, ICE 발산/수렴
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 · 276 lines · 31 tokens per session scan A e88a1bdbb35d
auto-idea is a skill published in the GitHub repository Insajin/autopus-adk (111 stars, last pushed today), licensed MIT. It adds 31 tokens to every session and 3,904 once invoked, about $0.0002 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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