daily-prep

작성자: github

내일의 회의와 작업을 준비합니다. WorkIQ를 통해 Outlook에서 일정을 가져오고, 열린 작업과 작업 공간 컨텍스트를 교차 참조하며, 회의를 분류합니다.

npx skills add https://github.com/github/awesome-copilot --skill daily-prep

Daily Prep

Generate a structured prep file for the next working day with meeting details, prep bullets, linked tasks, and productivity recommendations.

When to Use

  • End of day: "prepare me for tomorrow"
  • Any time: "prep me for Friday" or "what does March 25 look like?"
  • Weekly planning: run for multiple days

Procedure

1. Determine Target Date

If the user specifies a date, use it. Otherwise, default to tomorrow (current date + 1 day). If tomorrow is Saturday, default to Monday. If Sunday, default to Monday. Compute the output path: outputs/YYYY/MM/YYYY-MM-DD-prep.html

2. Pull Calendar via WorkIQ

Use the WorkIQ MCP tool to fetch the calendar. Ask WorkIQ:

"What meetings do I have on {target date}? For each meeting, include: subject, start time, end time, organizer, all attendees with their email addresses, location, whether it's online, and whether I've accepted or declined."

If the response is insufficient, make a follow-up query:

"For the meetings on {target date}, which ones are marked as optional or tentative? Which ones are recurring?"

3. Classify Each Meeting

Apply these labels based on attendee domains and subject:

LabelCriteria
[Customer · HIGH]External attendees from customer/partner domains, or subject matches a known customer name
[Internal]Only internal company domain attendees
[Community]CoP, community, guild, learning sessions
[Upskilling]Training, workshop, certification, learning
[Optional · skip]Tentative, low importance, or known recurring optional (e.g., "Office Hours", "Open Q&A")
[Personal]Private events, non-work

Zone Markers

For every meeting, check the organizer field and apply these additional markers:

ConditionMarkerAction
Starts ≥ 15:30 and < 16:00 (any organizer)⚠️ After-hoursRecommend decline
Starts ≥ 16:00 and not self-organized⚠️ After-hoursRecommend decline
Starts ≥ 16:00 and self-organized(no flag)OK — you chose to schedule it
Before 09:00 and not self-organized⚠️ EarlyRecommend decline — intrudes on learning window
Before 09:00 and self-organized(no flag)OK — you chose to schedule it
Overlaps 12:00–13:00🍽️ Lunch conflictNote in Calendar Notes

"Self-organized" means you are the meeting organizer (check the organizer field from WorkIQ).

4. Ideal Day Structure

Use this as the decision framework for all analysis steps. Every meeting must be evaluated against these zones. Users should adapt these times and targets to their personal routine.

ZoneTimePurposeRules
Morning FocusBefore 09:00Admin, learning, personal workProtect from others' meetings. Flag external events.
Customer Zone09:00–12:00Customer / external meetingsMax 2 customer meetings. Prefer mornings for external calls.
Lunch12:00–13:00BreakProtected. Flag any overlap.
Deep Work13:00–15:30Deliverables, focused coding/writingMinimize meetings. Flag non-essential meetings as deep work disruption.
Protected (strict)15:30–16:00End of day wind-downFlag all meetings regardless of organizer.
Protected (flex)16:00+End of dayFlag others' meetings only. Self-organized OK.

Targets per day:

  • Learning hours: 1.5h (from morning focus + gap time)
  • Deep work hours: 2.5h (13:00–15:30 zone)
  • Customer meetings: max 2 (preferably in 09:00–12:00)

5. Detect Conflicts & Day Fit Issues

Compare event time windows. Flag overlaps in a Conflicts table with a recommendation for each — prioritize customer meetings over internal/optional.

Also detect these day fit issues (report in a separate "Day Fit Issues" table):

CheckConditionFlag
Customer overload>2 [Customer · HIGH] meetingsFlag 3rd+ as "Consider rescheduling to another day"
Deep work disruptionNon-essential meetings in 13:00–15:30 zone"Disrupts deep work — consider moving to morning"
Non-ideal placementCustomer meetings outside 09:00–12:00"Customer meeting outside preferred morning zone"
Early intrusionOthers' meetings before 09:00"Intrudes on learning window — recommend decline"
Lunch conflictMeeting overlaps 12:00–13:00"Conflicts with lunch break"

6. Gather Context from Workspace

  1. Read open task files for tasks related to customer names or attendees in tomorrow's meetings
  2. Search workspace folders for recent files related to those customers or topics
  3. Check recent meeting summaries or plans for relevant prep context
  4. Use this to generate actionable prep bullets per meeting

7. Generate Prep per Meeting

For each meeting (chronological), include:

  • Time, subject, organizer
  • Attendee list (first name, company if external)
  • 3–5 actionable prep bullets based on open tasks, recent summaries, and meeting subject
  • If no context available, note what to ask/clarify in the meeting

8. Find Learning & Focus Slots

After generating prep per meeting, analyze the day's schedule to find open slots:

  1. Morning Focus confirmation — Verify the morning focus window is clear. If any non-self-organized event exists there, flag it.

  2. Learning Slots — Find gaps ≥ 30 min in the morning window and any other free slots suitable for upskilling. Target: 1.5h/day. For each slot: time range, duration, suggested activity.

  3. Deep Work Blocks — Find continuous free gaps in the 13:00–15:30 zone for deliverables. For each block: time range, duration, suggested task from open tasks.

  4. Report totals:

    • Learning hours found vs. 1.5h target (e.g., "1.0h / 1.5h target — 0.5h short")
    • Deep work hours available in 13:00–15:30 (e.g., "2.0h / 2.5h available")

9. Productivity Recommendations

Analyze the full day and provide:

SectionWhat to Include
Day Fit ScoreRate 0–100% how well the day matches the Ideal Day Structure. Criteria: (1) morning focus clear (+20%), (2) ≤2 customer meetings in 09:00–12:00 (+20%), (3) lunch 12:00–13:00 protected (+15%), (4) deep work 13:00–15:30 intact (+20%), (5) nothing after 15:30 or only self-organized after 16:00 (+15%), (6) ≥1h learning slots found (+10%). Show as: 🟢 ≥80%, 🟡 50–79%, 🔴 <50%.
Day ShapeTotal meeting hours, focus time available, learning hours, deep work hours, heavy/moderate/light assessment
Decline CandidatesAuto-include: (1) all meetings 15:30–16:00, (2) others' meetings ≥16:00, (3) others' meetings <09:00, (4) 3rd+ customer meeting, (5) optional meetings during deep work zone. Show "Reclaim" column with minutes recovered. Self-organized meetings before 09:00 or after 16:00 are excluded from auto-decline.
Conflict ResolutionSpecific recommendation for each overlap
Learning SlotsGaps for upskilling — from Step 8. Table: Window, Duration, Suggested Activity. Show total vs. 1.5h target.
Deep Work BlocksFree gaps in 13:00–15:30 for deliverables — from Step 8. Table: Window, Duration, Suggested Task.
Energy ManagementFlag if >3h back-to-back customer meetings without a break
Top 3 PrioritiesThe 3 most impactful things to accomplish (meetings + tasks combined)

10. Write the File

Create the output file at outputs/YYYY/MM/YYYY-MM-DD-prep.html as a self-contained HTML file with embedded CSS (dark theme, color-coded timeline, responsive layout).

If a file already exists for that date, read it first and update rather than overwrite — the user may have added manual notes.

Example Prompts

  • "Prepare me for tomorrow"
  • "What does Friday look like?"
  • "Daily prep for March 28"
  • "Prep me for next Monday — focus on customer meetings"

Requirements

  • WorkIQ MCP tool must be available for calendar access (Microsoft 365 / Outlook)
  • A workspace with task files and customer/project folders for context enrichment
  • Output is self-contained HTML — no external dependencies

github의 다른 스킬

console-rendering
github
Go에서 struct 태그 기반 콘솔 렌더링 시스템 사용 지침
official
acquire-codebase-knowledge
github
사용자가 기존 코드베이스에 대한 매핑, 문서화, 또는 온보딩을 명시적으로 요청할 때 이 스킬을 사용하세요. "이 코드베이스를 매핑해줘", "문서화해줘"와 같은 프롬프트에서 트리거됩니다.
official
acreadiness-assess
github
현재 리포
official
acreadiness-generate-instructions
github
AgentRC 명령어를 통해 맞춤형 AI 에이전트 지침 파일을 생성합니다. .github/copilot-instructions.md 파일을 생성합니다(기본값, VS Code의 Copilot에 권장됨).
official
acreadiness-policy
github
사용자가 AgentRC 정책을 선택, 작성 또는 적용할 수 있도록 지원합니다. 정책은 관련 없는 검사를 비활성화하고, 영향/수준을 재정의하며, 설정을 통해 준비 상태 점수를 사용자 지정합니다.
official
add-educational-comments
github
코드 파일에 교육용 주석을 추가하여 효과적인 학습 자료로 변환합니다. 설명의 깊이와 어조를 세 가지 설정 가능한 지식 수준(초급, 중급, 고급)에 맞게 조정합니다. 파일이 제공되지 않으면 자동으로 요청하며, 빠른 선택을 위해 번호 목록 매칭을 제공합니다. 교육용 주석만을 사용하여 파일을 최대 125%까지 확장합니다(엄격한 제한: 새 줄 400개, 1,000줄 초과 파일의 경우 300개). 파일 인코딩, 들여쓰기 스타일, 구문 정확성 등을 유지합니다.
official
adobe-illustrator-scripting
github
Adobe Illustrator 자동화 스크립트를 ExtendScript(JavaScript/JSX)로 작성, 디버깅 및 최적화합니다. 스크립트를 생성하거나 수정하여 조작할 때 사용합니다.
official
agent-governance
github
선언적 정책, 의도 분류, AI 에이전트 도구 접근 및 행동 제어를 위한 감사 추적. 구성 가능한 거버넌스 정책은 허용/차단된 도구, 콘텐츠 필터, 속도 제한, 승인 요구 사항을 정의하며, 코드가 아닌 구성으로 저장됨. 의미론적 의도 분류는 패턴 기반 신호를 사용하여 도구 실행 전에 위험한 프롬프트(데이터 유출, 권한 상승, 프롬프트 인젝션)를 탐지함. 도구 수준 거버넌스 데코레이터는 함수에서 정책을 적용함...
official