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 team-attention/plugins-for-claude-natives --skill tech-decisiongit clone --depth 1 https://github.com/team-attention/plugins-for-claude-nativesWrote 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/team-attention/plugins-for-claude-natives/tech-decision)<a href="https://agentmods.dev/skills/team-attention/plugins-for-claude-natives/tech-decision"><img src="https://agentmods.dev/badge/skills/team-attention/plugins-for-claude-natives/tech-decision/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/team-attention/plugins-for-claude-natives/tech-decision"><img src="https://agentmods.dev/badge/skills/team-attention/plugins-for-claude-natives/tech-decision.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 | $0.00099 | $0.01889 |
| Opus 5 | $0.00049 | $0.00945 |
| Sonnet 5 | $0.00020 | $0.00378 |
| Haiku 4.5 | $0.00010 | $0.00189 |
Grade A, and why
tech-decision 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 9d 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 — 210 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tech Decision - 기술 의사결정 깊이 탐색
기술적 의사결정을 체계적으로 분석하고 종합적인 결론을 도출하는 스킬.
핵심 원칙
두괄식 결과물: 모든 보고서는 결론을 먼저 제시하고, 그 다음에 근거를 제공한다.
사용 시나리오
- 라이브러리/프레임워크 선택 (React vs Vue, Prisma vs TypeORM)
- 아키텍처 패턴 결정 (Monolith vs Microservices, REST vs GraphQL)
- 구현 방식 선택 (Server-side vs Client-side, Polling vs WebSocket)
- 기술 스택 결정 (언어, 데이터베이스, 인프라 등)
의사결정 워크플로우
Phase 1: 문제 정의
의사결정 주제와 맥락을 명확히 한다:
- 주제 파악: 무엇을 결정해야 하는가?
- 옵션 식별: 비교할 선택지들은 무엇인가?
- 평가 기준 수립: 어떤 기준으로 평가할 것인가?
- 성능, 학습 곡선, 생태계, 유지보수성, 비용 등
- 프로젝트 특성에 맞는 기준 우선순위 설정
- 상세 기준은
references/evaluation-criteria.md참조
Phase 2: 병렬 정보 수집
여러 소스에서 동시에 정보를 수집한다. 반드시 병렬로 실행:
┌─────────────────────────────────────────────────────────────┐
│ 동시 실행 (Task tool로 병렬 실행) │
├─────────────────────────────────────────────────────────────┤
│ 1. codebase-explorer agent │
│ → 기존 코드베이스 분석, 현재 패턴/제약사항 파악 │
│ │
│ 2. docs-researcher agent │
│ → 공식 문서, 가이드, best practices 리서치 │
│ │
│ 3. Skill: dev-scan │
│ → 커뮤니티 의견 수집 (Reddit, HN, Dev.to, Lobsters) │
│ │
│ 4. Skill: agent-council │
│ → 다양한 AI 전문가 관점 수집 │
│ │
│ 5. [선택] Context7 MCP │
│ → 라이브러리별 최신 문서 조회 │
└─────────────────────────────────────────────────────────────┘
실행 방법:
# Agents는 Task tool로 병렬 실행
Task codebase-explorer: "분석할 주제와 컨텍스트"
Task docs-researcher: "리서치할 기술/라이브러리"
# 기존 스킬은 Skill tool로 호출
Skill: dev-scan (커뮤니티 의견)
Skill: agent-council (전문가 관점)
What ships with it
2 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.
- 9d ago First seen · 210 lines · 99 tokens per session scan A 72c56b41cf9e
tech-decision is a skill published in the GitHub repository team-attention/plugins-for-claude-natives (824 stars, last pushed 4mo ago), licensed MIT. It adds 99 tokens to every session and 1,889 once invoked, about $0.0005 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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