agentleFS
southglorysouthglory/system-agents-template/skills/send-message/SKILL.md

send-message

Skill2 starsChanged 4 months agoMITView on GitHub

에이전트 간 채팅방에 메시지를 보낸다. 인자로 채팅방 이름을 받는다.

2 other projects use a version of this.

Adopted by

Most recently taken up by

  • Other versions2 projects use a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 2

    1. Arasz/ai-badger★ 3same name
    2. srobinson/nancy★ 0same name

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository10 other files it gives its agents.

The file

Files
SKILL.md

채팅방에 메시지 보내기

채팅방: $ARGUMENTS

절차

  1. 내 이름을 확인한다 (role.md 또는 현재 프로젝트 디렉토리에서 판단)
  2. chatrooms 디렉토리를 찾는다. 현재 프로젝트의 상위에 chatrooms/ 폴더가 있어야 한다.
  3. 파일명을 결정한다.
    • 규칙: {날짜}_{시분초}_{에이전트명}.md
    • 날짜: UTC 기준 YYYY-MM-DD
    • 시분초: UTC 기준 HHMMSS (6자리)
    • 에이전트명: 소문자
    • 예: 2026-03-19_143052_alice.md
  4. 사용자에게 메시지 내용과 type을 확인한다 (대화 맥락에서 명확하면 바로 진행)
  5. type별 필수 필드를 검증한다:

    type필수 필드
    messagefrom, to, time, type, subject
    task-createfrom, to, time, type, subject, goal, phase, assignee, priority, due
    task-updatefrom, to, time, type, subject, ref
    task-donefrom, to, time, type, subject, ref
    task-claimfrom, to, time, type, subject, ref
    turn-endfrom, to, time, type, subject
    • 필수 필드가 빠져 있으면 사용자에게 물어본다
    • 유효하지 않은 type이면 메시지를 보내지 않고 사용자에게 알린다
  6. type에 맞는 메시지 파일을 생성한다:

message

---
from: {내 이름}
to: {상대 또는 all}
time: {YYYY-MM-DD HH:MM:SS UTC}
type: message
subject: {제목}
mentions: [{멘션 대상}]
---

{본문}

task-create

---
from: {내 이름}
to: all
time: {YYYY-MM-DD HH:MM:SS UTC}
type: task-create
subject: {작업 제목}
goal: {소속 목표}
phase: {소속 단계}
assignee: {담당자}
priority: {high/medium/low}
due: {YYYY-MM-DD}
---

{상세 설명}

task-update

---
from: {내 이름}
to: all
time: {YYYY-MM-DD HH:MM:SS UTC}
type: task-update
subject: {변경 설명}
ref: {작업 ID, 예: T-001}
status: {변경할 상태}
---

{사유}

task-done

---
from: {내 이름}
to: all
time: {YYYY-MM-DD HH:MM:SS UTC}
type: task-done
subject: {완료 보고}
ref: {작업 ID}
---

{완료 내용 요약}

task-claim

---
from: {내 이름}
to: all
time: {YYYY-MM-DD HH:MM:SS UTC}
type: task-claim
subject: {작업 ID} 선점
ref: {작업 ID}
---

{선점 사유 또는 계획}
  1. 자신의 .read-status/{내이름}.json을 업데이트하여 방금 보낸 파일을 마지막 읽은 것으로 기록한다.
  2. 사용자에게 전송 완료를 알린다. type이 task-* 계열이면 "봇이 다음 Phase에서 처리합니다"라고 안내한다.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.