three.js로 입체 모델을 만들고 회전 가능한 뷰어에서 모든 각도로 확인합니다. OBJ + MTL이나 GLB로 저장해 다른 3D 제작 소프트웨어에서 사용할 수 있습니다.
- 입체 모델을 만들고 모든 각도에서 확인하기
- Blender에서 편집할 모델 만들기
- 모델의 윤곽과 재질 표현 확인하기
여러 정보원을 조사해 선택지 비교와 시장 및 연구 동향을 읽기 쉬운 보고서로 정리합니다. 주제별로 조사를 나누어 맡기고 수집한 정보를 통합합니다.
Use this skill when the user's prompt requires (1) researching a topic across multiple sources, comparing options or alternatives, analyzing trends or history, understanding markets or industries, or reviewing literature or studies and (2) synthesizing that research into a comprehensive, narrative report. If you're planning to search the web or internal knowledge bases, consider using this skill. This skill coordinates research subagents, so use it only when you have a tool for spawning subagents (the Agent or Task tool); otherwise, research the question directly.
실행 점수 미검증
설치 방법 보기여러 정보원으로 질문을 조사하고 결과를 읽기 쉬운 하나의 보고서로 정리합니다. 질문을 독립적인 주제로 나누고 서브에이전트라는 별도의 작업 담당자에게 병렬로 조사를 맡깁니다. 필요하면 부족한 정보를 보완한 뒤 작성 담당자가 조사 메모를 통합합니다. 조사 메모와 완성된 보고서는 각각의 폴더에 저장합니다.
제품이나 서비스 비교, 시장과 업계 이해, 역사나 추세 분석, 연구 문헌 정리에 적합합니다. 이전 조사를 갱신할 때는 과거 보고서를 배경 자료로 삼고 추가로 필요한 내용을 조사합니다. 대상 지역이나 용어가 모호하여 조사에 영향을 주는 경우 먼저 확인합니다.
서브에이전트를 시작할 수 있는 Agent 또는 Task 도구가 필요합니다. 지원 도구가 없는 환경에서는 이 스킬로 조사를 분담하지 않고 질문을 직접 조사하는 방식을 전제로 합니다.
이 소개문은 공개된 SKILL.md를 바탕으로 AI(OpenAI Codex)가 작성했습니다. 정확한 사양은 아래 원문을 확인하세요.
AI가 SKILL.md의 내용에서 주의가 필요한 작업과 도입 전제를 확인했습니다. 점수는 실제로 실행한 결과(실행 검증)만으로 매깁니다.
점수에는 넣지 않았습니다. 2026년 10월 24일 기준으로 AI(OpenAI Codex)가 판정했습니다. 참고용이므로 설치 전에 원문도 확인해 주세요.
설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
You are acting as the coordinator. Your job is to analyze the user's question, spawn subagents, and manage output files. In order to keep your context clean, you should never conduct research or write files directly. For the same reason, you also should not read the researcher.md or report-writer.md files.
As you work, if you have a to-do or task-list tool (for example TodoWrite, or TaskCreate and TaskUpdate), use it to keep the user informed of your plan and progress. For clarity, don't reference subagents in those items. For example, you might say "Conduct research" instead of "Spawn research subagents".
Read the user's question and consider if there are any missing or ambiguous details that need to be clarified. Some examples include:
In order to avoid creating unnecessary friction with the user, follow ups should only be asked when they would meaningfully impact how research is conducted.
If you determine that you do need to ask follow up questions, do so with the AskUserQuestion tool.
First choose a title for this research. It names the folder that will hold this request's research notes and is also the filename of the report the user receives, where it is shown as the report's title, so make it a short, specific title for this research in the user's language and in sentence case: 3 to 6 words and under 50 characters (count them, and drop words rather than exceed either limit), using only letters, numbers and single spaces. Keep accented and non-Latin letters exactly as the user's language writes them (for example é, ñ, ü, 日本語) rather than converting them to plain ASCII, and use no hyphens, underscores, apostrophes or other punctuation. For example, a question about how the EU AI Act affects startups could use "EU AI Act startup obligations".
This research's folders go in the same directory you used for research earlier in this conversation, or, if this is the first research request here, in your current working directory (not /tmp or an uploads folder). Before settling on the title, recall the titles of any research reports you have already delivered earlier in this conversation, and, if a research_notes/ folder already exists in that directory, list it — each folder inside it holds the notes behind a report of the same name in reports/, possibly from an earlier conversation. Then pick the case that fits:
In every case the title must differ from every report delivered earlier in this conversation and from every folder you see, so that this request's notes and report never mix with or replace an earlier one's. Never rename, move or write into an earlier request's folder.
Then create the folders research_notes/{research title}/ and reports/ in that directory. Quote these paths in shell commands, since the title contains spaces, and note the directory's absolute path — you will give the subagents absolute paths into these folders, and they will store their files there.
In order to effectively spawn and task subagents, determine if and how the user's question can be decomposed into independent subtopics. These subtopics should be mutually exclusive and collectively exhaustive. For each subtopic, then consider if the research requires (or would benefit from) multiple independent points of view.
| Researchers | Decomposition Strategy | Example |
|---|---|---|
| 1 | No meaningful decomposition — single factual question | "Who won the 2024 Super Bowl?" |
| 3 | Few natural angles or perspectives on a focused topic | "Effects of temperature on salmon migration" → (1) biological mechanisms, (2) observed population data, (3) climate projections |
| 4 | Distinct facets or evaluation criteria | "Compare CRM platforms for small businesses" → (1) pricing models, (2) feature comparison, (3) integrations ecosystem, (4) user reviews/sentiment |
| 5 | Multiple independent entities, regions, or domains | "AI regulation landscape" → (1) US federal, (2) EU/GDPR-AI Act, (3) China, (4) UK, (5) industry self-regulation |
| 6+ | Large enumerable set requiring systematic coverage | "Electric vehicle adoption rates by US state" → researchers assigned to regional clusters |
In the next step, you should spawn one subagent for each subtopic and independent point of view that you identified. When in doubt, 3 researchers is a reasonable default. If in step 2 you noted earlier research to build on, decompose only what this request adds or needs re-checked; the report writer will have the earlier material.
For each subtopic and independent point of view determined above, spawn a foreground research subagent.
To spawn research subagents, use the Agent tool (named Task in some versions) with subagent_type="general-purpose" and run_in_background=false. Ensure that you provide extremely clear, specific instructions to each research subagent. Be sure to propagate constraints of the original question to the research subagent (e.g., temporal, geographical). In the prompts below, replace {path_to_skill} with this skill's base directory (the directory this SKILL.md was loaded from), {absolute path of your working directory} with the path you noted in step 2, and {research title} with the title you chose in step 2. Follow the exact format provided below:
Agent(
run_in_background=false
subagent_type="general-purpose",
description="{3-5 words}",
prompt="Research {specific narrow topic}.
Objective: {clear description of what's covered in the desired output}
Key questions:
- {Specific question 1}
- {Specific question 2}
Suggested sources:
- {Types of source to prioritize}
Constraints:
- {Any bounds from the initial user query, including temporal or geographic}
Save your output notes to {absolute path of your working directory}/research_notes/{research title}/{topic}.md
**As a first step, you must read {path_to_skill}/references/researcher.md for instructions on how to conduct research.**"
)
Example of a good, clear, detailed prompt for a research subagent:
Research the semiconductor supply chain crisis and its current status as of 2026.
Objective: Compile a dense report of the facts, covering the current situation, ongoing solutions, and future outlook, with specific timelines and quantitative data where available.
Key questions:
- What are current bottlenecks?
- What are the projected capacity increases from new fab construction?
- What are geopolitical factors affecting supply chains?
- When do experts predict supply will meet demand?
Suggested sources:
- Recent quarterly reports from major chip manufacturers like TSMC, Samsung, and Intel, found on investor relations pages or through the SEC EDGAR database
- Industry reports from SEMI, Gartner, and IDC that provide market analysis and forecasts
- Government responses, including US CHIPS Act implementation progress at commerce.gov, EU Chips Act at ec.europa.eu, and similar initiatives in Japan, South Korea, and Taiwan through their respective government portals
Constraints:
- Must reflect current state as of 2026 with prior issues clearly noted as such
Save your output notes to {absolute path of your working directory}/research_notes/Semiconductor supply chain outlook 2026/semiconductor_supply_chain.md
As a first step, you must read {path_to_skill}/references/researcher.md for instructions on how to conduct research."
In order to ensure research is conducted as quickly as possible, it's essential that all subagents are spawned in parallel, i.e., that you make all your calls to the Agent tool in a single turn.
Based on the task summaries returned by the research subagents, determine if there are any critical gaps that would make the report incomplete. If deemed absolutely necessary, spawn researchers in parallel to close those gaps. Spawning additional researchers in this step delays delivery of the report to the user, leading to a much worse experience, so this must be used with extreme care.
This step can only be followed once - after the researchers finish, move immediately to Step 6, regardless of what results you get back. If you kick off any more research, you will hit timeouts or rate limits, meaning the user will never get an answer to their query. To help yourself remember this, you should always output "After these researchers finish, I will move directly to coordinating the report writer" when choosing to kick off additional research.
After research is done, spawn a single report writer subagent. Use the Agent tool (named Task in some versions) with subagent_type="general-purpose" and run_in_background=false, and fill in the placeholders as in step 4. For {the user's original question}, state the question this report must answer in full — if this request returns to or extends earlier research, that is the earlier question as amended by this request (for example "How does the EU AI Act affect startups, including penalties?"), not just the follow-up message. On the line for earlier research, give the absolute paths of the earlier report and notes folder you noted in step 2, or write "none" if you noted nothing to build on or the user asked for an independent redo. Follow the exact format provided below:
Agent(
run_in_background=false
subagent_type="general-purpose",
description="Write final report",
prompt="Read the notes in {absolute path of your working directory}/research_notes/{research title}/ and synthesize into a research report that answers: {the user's original question}.
Earlier research in this conversation to build on: {absolute paths of the earlier report and notes folder from step 2, or "none"}
Save your final report to this exact path: {absolute path of your working directory}/reports/{research title}.md
**As a first step, you must read {path_to_skill}/references/report-writer.md for instructions on how to write your research report.**"
)
After the report writer is done, make the report available to the user: if you have a tool for sending files to the user (for example SendUserFile), send reports/{research title}.md with it; otherwise, if your environment has a user-visible outputs folder, copy the report there under the same filename; otherwise leave it at reports/{research title}.md. Then read the finalized report and send the user a brief summary (aim for 3-5 sentences) that says where the full report is (sent to them, in the outputs folder, or its absolute path).
아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
three.js로 입체 모델을 만들고 회전 가능한 뷰어에서 모든 각도로 확인합니다. OBJ + MTL이나 GLB로 저장해 다른 3D 제작 소프트웨어에서 사용할 수 있습니다.
개인 작업 목록에 할 일, 기한, 다음 단계, 답변을 기다리는 대상과 진행을 막는 이유를 기록합니다. 진행 상황과 의존 관계를 갱신하고 중복 및 완료 항목을 정리합니다.
Coordinate a task from a verifiable goal through completion. Handle work directly or split independent tasks across separate agent sessions, track progress, verify results, and arrange pull request merging when included in the goal.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
재생, 일시 정지, 시간 위치 지정이 가능한 HTML 애니메이션을 만듭니다. 장면 길이와 속도를 조절하고 가로형·세로형 영상 내보내기를 준비합니다.
Apple Health에 동기화된 걸음 수, 심박수, 수면, 운동 기록을 기간별로 확인하고 일상 변화와 동기화 상태, 누락된 데이터를 살펴봅니다.
Word 문서와 템플릿을 만들고 편집하며 내용 추출, 이미지 교체, 변경 내용 추적과 메모를 다룹니다. 제목과 목록 구조를 정리하고 모든 페이지의 표시를 확인합니다.