소스 정보
- 저장소
- jmagly/aiwg
- 최근 소스 활동
- 2026년 4월 30일 21:57
- 감지된 SKILL.md 언어
- 영어
- 스타
- 178
- 포크
- 26
설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/jmagly/aiwg --skill research-document명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SKILL.md 표시 중
SOC 직업 분류 기준
| namespace | aiwg |
| name | research-document |
| platforms | ["all"] |
| description | Generate summaries and literature notes from research papers |
| commandHint | {"argumentHint":"[REF-XXX] [--depth brief|standard|comprehensive]","category":"research-documentation"} |
Generate structured summaries and literature notes from acquired research papers.
When invoked, create comprehensive documentation:
Load Paper
.aiwg/research/sources/Extract Content
Analyze Relevance
Generate Documentation
Create Synthesis Notes
.aiwg/research/literature-notes/REF-XXX-notes.mdUpdate Index
[ref-id] - REF-XXX identifier (required)--depth [brief|standard|comprehensive] - Documentation depth (default: standard)--focus [section] - Focus on specific section (methodology, results, implications)--update-only - Update existing documentation rather than regenerate--include-citations - Extract all citations from paper for potential acquisition| Level | Content |
|---|---|
brief | Executive summary + key findings only (~500 words) |
standard | Full finding document with all sections (~1500 words) |
comprehensive | Full document + literature notes + citation extraction (~3000 words) |
# Standard documentation
/research-document REF-022
# Brief summary for quick review
/research-document REF-022 --depth brief
# Comprehensive with citation extraction
/research-document REF-022 --depth comprehensive --include-citations
# Update existing documentation
/research-document REF-022 --update-only
# Focus on methodology only
/research-document REF-022 --focus methodology
Documenting: REF-022 - AutoGen: Enabling Next-Gen LLM Applications
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Step 1: Loading paper
✓ PDF loaded (27 pages)
✓ Metadata parsed
✓ Existing finding document found
Step 2: Extracting content
✓ Abstract extracted
✓ Sections parsed: Introduction, Framework, Evaluation, Discussion
✓ 4 key findings identified
✓ 12 figures/tables extracted
✓ 3 direct quotes captured
Step 3: Analyzing AIWG relevance
✓ High relevance to agent orchestration
✓ Applicable to: Conversable Agent Interface, Auto-Reply Chains
✓ Implementation priority: HIGH
✓ Maps to: UC-174, UC-183
Step 4: Generating documentation
✓ Finding document updated: .aiwg/research/findings/REF-022-autogen.md
✓ Sections populated:
- Executive Summary (150 words)
- Key Findings (4 findings, metrics included)
- Methodology (multi-agent conversational framework)
- AIWG Relevance (applicable components listed)
- Implementation Notes (integration patterns)
- Limitations (scalability concerns noted)
- References (45 citations)
Step 5: Creating synthesis notes
✓ Literature note: .aiwg/research/literature-notes/REF-022-notes.md
✓ Connected to: REF-001, REF-013, REF-057
✓ Synthesis themes: agent collaboration, HITL patterns
✓ Follow-up questions: 3 identified
Step 6: Updating indices
✓ Added to topic indices: agentic-workflows, multi-agent-systems
✓ Cross-reference map updated
✓ Flagged for next synthesis report
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Documentation complete!
Finding: .aiwg/research/findings/REF-022-autogen.md (1,847 words)
Literature Note: .aiwg/research/literature-notes/REF-022-notes.md (623 words)
Next Steps:
1. /research-quality REF-022 - Assess evidence quality
2. /research-cite REF-022 - Generate citations
3. Review AIWG integration opportunities in UC-174, UC-183
Documentation includes automatic quality checks:
Documentation follows AIWG voice guidelines:
Avoids: