This skill should be used when the user asks to "기술 의사결정", "뭐 쓸지 고민", "A vs B", "비교 분석", "라이브러리 선택", "아키텍처 결정", "어떤 걸 써야 할지", "트레이드오프", "기술 선택", "구현 방식 고민", or needs deep analysis for technical…

MITAuto-check passedBackend & APIs

Install Tech Decision

skills CLI
$ npx skills add team-attention/plugins-for-claude-natives --skill tech-decision -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install team-attention/plugins-for-claude-natives tech-decision --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/team-attention/plugins-for-claude-natives.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/dev/skills/tech-decision .claude/skills/tech-decision && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
tech-decision
GitHub stars
825
Used in
3 other repos
Token cost
~1.2k tokens
SKILL.md length
300 words
Files
3 (incl. references)
Skills in repo
16
Repo updated
First seen
Licence
MIT

At a glance

This skill should be used when the user asks to "기술 의사결정", "뭐 쓸지 고민", "A vs B", "비교 분석", "라이브러리 선택", "아키텍처 결정", "어떤 걸 써야 할지", "트레이드오프", "기술 선택", "구현 방식 고민", or needs deep analysis for technical…

  • Works in 7 steps: 문제 정의 → 병렬 정보 수집 → 종합 분석 → …
  • Asks to 기술 의사결정
  • SKILL.md covers 핵심 원칙, 사용 시나리오, 의사결정 워크플로우 and 활용하는 리소스, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Tech Decision is an agent skill from team-attention/plugins-for-claude-natives. This skill should be used when the user asks to "기술 의사결정", "뭐 쓸지 고민", "A vs B", "비교 분석", "라이브러리 선택", "아키텍처 결정", "어떤 걸 써야 할지", "트레이드오프", "기술 선택", "구현 방식 고민", or needs deep analysis for technical decisions. Provides systematic multi-source research and synthesized recommendations.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/evaluation-criteria.md` and `references/report-template.md`).

It sits in Backend & APIs, covering Deep research. The repository describes itself as: Claude Code plugins for power users. The licence is MIT.

When your agent uses it

  • Asks to 기술 의사결정
  • Needs deep analysis for technical decisions

Example prompts

  • “A vs B”
  • “/tech-decision”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. 문제 정의
  2. 병렬 정보 수집
  3. 종합 분석
  4. 최종 보고서 생성
  5. 간단한 비교 (A vs B)
  6. 깊은 분석 (복잡한 의사결정)
  7. 아키텍처 결정

What it can do on your machine

Read from SKILL.md and the folder at commit fd9c207. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Tech Decision loads about 1.2k tokens when it runs, and up to ~3.7k if it reads all its reference files. Until then it costs about 73 tokens; SKILL.md has 300 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~73
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from team-attention/plugins-for-claude-natives at commit fd9c207, republished under its MIT licence (© team-attention). 300 words, ~1,214 tokens.

Download SKILL.mdSave it as .claude/skills/tech-decision/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
tech-decision
description
This skill should be used when the user asks to "기술 의사결정", "뭐 쓸지 고민", "A vs B", "비교 분석", "라이브러리 선택", "아키텍처 결정", "어떤 걸 써야 할지", "트레이드오프", "기술 선택", "구현 방식 고민", or needs deep analysis for technical decisions. Provides systematic multi-source research and synthesized recommendations.
version
0.1.0

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:

  1. 주제 파악: 무엇을 결정해야 하는가?
  2. 옵션 식별: 비교할 선택지들은 무엇인가?
  3. 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.md 참조
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:

markdown
# 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)
Phase 3: 종합 분석

수집된 정보를 바탕으로 tradeoff-analyzer agent를 실행:

  • 각 옵션별 pros/cons 정리
  • 평가 기준별 점수화
  • 충돌하는 의견 정리
  • 신뢰도 평가 (출처 기반)
Phase 4: 최종 보고서 생성

decision-synthesizer agent로 두괄식 종합 보고서 작성 (상세 템플릿: references/report-template.md):

markdown
# 기술 의사결정 보고서: [주제]

## 결론 (Executive Summary)
**추천: [Option X]**
[1-2문장 핵심 이유]

## 평가 기준 및 가중치
| 기준 | 가중치 | 설명 |
|------|--------|------|
| 성능 | 30% | ... |
| 학습곡선 | 20% | ... |

## 옵션별 분석

### Option A: [이름]
**장점:**
- [장점 1] (출처: 공식 문서)
- [장점 2] (출처: Reddit r/webdev)

**단점:**
- [단점 1] (출처: HN 토론)

**적합한 경우:** [시나리오]

### Option B: [이름]
...

## 종합 비교
| 기준 | Option A | Option B | Option C |
|------|----------|----------|----------|
| 성능 | ⭐⭐⭐ | ⭐⭐ | ⭐⭐⭐⭐ |
| 학습곡선 | ⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐ |
| **총점** | **X점** | **Y점** | **Z점** |

## 추천 근거
1. [핵심 근거 1 with 출처]
2. [핵심 근거 2 with 출처]
3. [핵심 근거 3 with 출처]

## 리스크 및 주의사항
- [주의점 1]
- [주의점 2]

## 참고 출처
- [출처 목록]

활용하는 리소스

Agents (이 플러그인)
Agent역할
codebase-explorer기존 코드베이스 분석, 패턴/제약사항 파악
docs-researcher공식 문서, 가이드, best practices 리서치
tradeoff-analyzer옵션별 pros/cons 정리, 비교 분석
decision-synthesizer두괄식 최종 보고서 생성
기존 스킬 (Skill tool로 호출)
Skill용도호출 방법
dev-scanReddit, HN, Dev.to 등 커뮤니티 의견Skill: dev-scan
agent-council다양한 AI 전문가 관점 수집Skill: agent-council
MCP (선택적)
  • Context7: 라이브러리별 최신 공식 문서 조회

빠른 실행 가이드

1. 간단한 비교 (A vs B)
사용자: "React vs Vue 뭐가 나을까?"

실행:
1. Task docs-researcher + Task codebase-explorer (병렬)
2. Skill: dev-scan
3. Task tradeoff-analyzer
4. Task decision-synthesizer
2. 깊은 분석 (복잡한 의사결정)
사용자: "우리 프로젝트에 상태관리 라이브러리 뭘 쓸지 고민이야"

실행:
1. Task codebase-explorer (현재 상태 분석)
2. 병렬 실행:
   - Task docs-researcher (Redux, Zustand, Jotai, Recoil 등)
   - Skill: dev-scan
   - Skill: agent-council
3. Task tradeoff-analyzer
4. Task decision-synthesizer
3. 아키텍처 결정
사용자: "모놀리스 vs 마이크로서비스 어떻게 해야 할까?"

실행:
1. Task codebase-explorer (현재 규모/복잡도 분석)
2. 병렬 실행:
   - Task docs-researcher (각 아키텍처 best practices)
   - Skill: agent-council (아키텍트 관점)
3. Task tradeoff-analyzer (팀 규모, 배포 복잡도 등 고려)
4. Task decision-synthesizer

주의사항

  1. 컨텍스트 제공: 프로젝트 특성, 팀 규모, 기존 기술 스택 등 맥락 정보가 많을수록 정확한 분석 가능
  2. 평가 기준 확인: 사용자에게 중요한 기준이 무엇인지 먼저 확인
  3. 신뢰도 표시: 출처가 불분명하거나 오래된 정보는 명시
  4. 결론 먼저: 항상 두괄식으로 결론부터 제시

추가 리소스

참고 파일
  • references/report-template.md - 상세 보고서 템플릿
  • references/evaluation-criteria.md - 평가 기준 가이드

© team-attention, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in plugins/dev/skills/tech-decision of team-attention/plugins-for-claude-natives.

  • SKILL.md
  • references/evaluation-criteria.md
  • references/report-template.md

Open the folder on GitHubat commit fd9c207

Used in 3 other repositories

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in team-attention/plugins-for-claude-natives, which our catalogue first saw on October 7, 2026.

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Questions about Tech Decision

What does Tech Decision do?

This skill should be used when the user asks to "기술 의사결정", "뭐 쓸지 고민", "A vs B", "비교 분석", "라이브러리 선택", "아키텍처 결정", "어떤 걸 써야 할지", "트레이드오프", "기술 선택", "구현 방식 고민", or needs deep analysis for technical…. Tech Decision is an agent skill from team-attention/plugins-for-claude-natives. This skill should be used when the user asks to "기술 의사결정", "뭐 쓸지 고민", "A vs B", "비교 분석", "라이브러리 선택", "아키텍처 결정", "어떤 걸 써야 할지", "트레이드오프", "기술 선택", "구현 방식 고민", or needs deep analysis for technical decisions.

When should I use Tech Decision?

Tech Decision fits situations like: asks to 기술 의사결정; needs deep analysis for technical decisions.

How do I install Tech Decision in Claude Code?

Run `npx skills add team-attention/plugins-for-claude-natives --skill tech-decision -a claude-code`. Or copy the skill folder (plugins/dev/skills/tech-decision in team-attention/plugins-for-claude-natives) into .claude/skills/tech-decision in your project. Claude Code loads it when a task matches its description.

How do I install Tech Decision in Codex?

Run `npx skills add team-attention/plugins-for-claude-natives --skill tech-decision -a codex`. Or copy the skill folder (plugins/dev/skills/tech-decision in team-attention/plugins-for-claude-natives) into .agents/skills/tech-decision in your project. Codex loads it when a task matches its description.

Can I use Tech Decision in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add team-attention/plugins-for-claude-natives --skill tech-decision -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tech-decision, .gemini/skills/tech-decision, .github/skills/tech-decision and .opencode/skills/tech-decision in your project.

What does Tech Decision need to run?

SKILL.md names no scripts, command-line tools or credentials: Tech Decision is instructions for the agent only.

Does Tech Decision access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Tech Decision safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Tech Decision use?

Tech Decision is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tech Decision use?

About 1.2k tokens (SKILL.md is roughly 4.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.4k tokens, read only when the agent opens those files.

What are the alternatives to Tech Decision?

Skills that share tags, products or a category with Tech Decision: Tech Decision (team-attention/hoyeon, 173 stars), Customs Trade Law Onur Kafkas (lawve-ai/awesome-legal-skills, 826 stars), Claude To Medrixflow (Citrus-bit/Anaxa, 120 stars) and GitHub Deep Research (bytedance/deer-flow, 83k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tech Decision?

team-attention (a GitHub organization) maintains it in team-attention/plugins-for-claude-natives, which has 825 GitHub stars. The repository holds 16 skills in this directory. The repository was last updated on April 20, 2026.

Source: team-attention/plugins-for-claude-natives on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.