Borrowing it
Nothing to install: this file belongs to fivetaku/idea-lab. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/fivetaku/idea-lab/main/.claude/commands/wrap.mdgit clone --depth 1 https://github.com/fivetaku/idea-labWrote 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/commands/fivetaku/idea-lab/wrap)<a href="https://agentmods.dev/commands/fivetaku/idea-lab/wrap"><img src="https://agentmods.dev/badge/commands/fivetaku/idea-lab/wrap/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/commands/fivetaku/idea-lab/wrap"><img src="https://agentmods.dev/badge/commands/fivetaku/idea-lab/wrap.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00139 | $0.00902 |
| Opus 5.5 | $0.00056 | $0.00361 |
| Sonnet 5.5 | $0.00028 | $0.00180 |
| Haiku 4.5 | $0.00014 | $0.00090 |
Grade A, and why
wrap 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 2mo 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
/wrap
세션을 마무리합니다: 기록 누락 점검 → 재사용 가치 산출물의 지식 승격(자산화) → 인덱스 갱신 → 한 줄 보고.
매 세션 이걸 돌리면 결과물이 흩어지지 않고 20-knowledge/에 온톨로지처럼 쌓여, 다음 아이데이션·기획이 그 위에서 시작됩니다.
실행 흐름
Step 1: 세션 변경 스캔
이번 세션에서 만들어지거나 바뀐 파일을 폴더별로 집계합니다 (30-research/, 40-ideas/, 50-planning/, 60-output/, 20-knowledge/).
Step 2: 기록 누락 점검
- 아이데이션을 했는데 아이데이션 기록·백로그가 갱신 안 됐으면 →
/ideation-wrap을 먼저 수행합니다. - 리서치 원자료에 출처·수집일이 빠졌으면 → 보완합니다.
- 기획서 초안에 근거 인용이 빠졌으면 → 그 사실을 보고합니다 (몰래 채우지 않음).
- 판정에 기준 번호가 빠진 곳이 있으면 → 보완합니다.
Step 3: 지식 승격 (자산화 — 핵심)
이번 세션 산출물 중 다음 업무에서 다시 꺼내 쓸 것을 후보로 제시합니다:
- 확정된 기획서·캠페인안 (60-output) — 과거 사례로서의 가치
- 정제된 리서치 리포트 — 시장·경쟁사 지식으로서의 가치
- 아이데이션에서 확정된 방향·결정 — 우리 팀의 판단 이력
- 반복 인용된 자료
후보마다 "왜 지식이 되는지 + 언제 다시 참조될지" 한 줄과 함께 보여주고, 사용자가 승인한 것만 20-knowledge/으로 복사·등재합니다. 이미 등재된 파일은 건너뜁니다 (멱등).
Step 4: 인덱스 갱신
20-knowledge/_index.md를 갱신합니다 (/kb-update와 같은 규칙):
- 새로 승격된 파일의 행 추가 — 무엇인지 / 출처 / 넣은 날짜 / 태그·관련 / 언제 참조
- 태그·관련 열이 온톨로지 역할을 합니다:
#캠페인 · 관련: 고객-정의서.md처럼 주제 태그와 연결 파일을 적어 두면, 다음 기획 때 관련 지식을 연쇄로 따라갈 수 있습니다. - 인덱스↔실제 파일 대조로 깨진 행(삭제된 파일)을 정리합니다.
Step 5: 한 줄 보고
## 세션 정리 완료
- 이번 세션: 리서치 N건 / 아이데이션 N건 / 기획서 N건 / 확정 N건
- 지식 승격: N건 → 20-knowledge/ (인덱스 갱신됨)
- 미결: (보류 재검토 예정일, 확인 필요 항목 등)
다음에 이어서 하려면: "..."라고 말하세요.
참조
20-knowledge/_index.md30-research/,40-ideas/,50-planning/,60-output/
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.
- 2mo ago First seen · 58 lines · 139 tokens per session scan A f636f5158686
wrap is a command published in the GitHub repository fivetaku/idea-lab (2 stars, last pushed 1mo ago), licensed MIT. It adds 139 tokens to every session and 902 once invoked, about $0.0006 per session on Opus 5.5. 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 2026-08-31.
Other commands, from other repositories
init-workspace-flow-questions
Phase 8 Questions of init-workspace-flow.
lesson-capture
Record structured lessons after significant tasks. Builds a persistent knowledge base that improves future agent performance. Run with an optional summary or use review to read past lessons.
export-clean
Strip internal-only elements (version drawer, review notes) from a staging HTML file to produce a clean export ready for CMS upload or public sharing.
growth-plan
Turn diagnosis into a sized greenfield opportunity map + a sequenced, mechanism-driven capture plan to overtake competitors.
keyword-research
You are a senior SEO & Content Marketing specialist. The user needs help with keyword research in the context of keyword research, content audits, serp analysis, technical seo and content strategy.
link-prospecting
You are a senior SEO & Content Marketing specialist. The user needs help with link prospecting in the context of keyword research, content audits, serp analysis, technical seo and content strategy.