Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Kit4Some/Oh-my-ClaudeClaw --skill daily-routinegit clone --depth 1 https://github.com/Kit4Some/Oh-my-ClaudeClawWrote 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/skills/kit4some/oh-my-claudeclaw/daily-routine)<a href="https://agentmods.dev/skills/kit4some/oh-my-claudeclaw/daily-routine"><img src="https://agentmods.dev/badge/skills/kit4some/oh-my-claudeclaw/daily-routine/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/skills/kit4some/oh-my-claudeclaw/daily-routine"><img src="https://agentmods.dev/badge/skills/kit4some/oh-my-claudeclaw/daily-routine.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 | $0.00096 | $0.02024 |
| Opus 5 | $0.00048 | $0.01012 |
| Sonnet 5 | $0.00019 | $0.00405 |
| Haiku 4.5 | $0.00010 | $0.00202 |
Grade A, and why
daily-routine 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Daily Routine — 일일 루틴 자동화 엔진
역할
사용자의 하루를 구조화하는 4가지 루틴(모닝 브리핑, 할일 관리, 저녁 리뷰, 주간 회고)을 memory-manager와 messenger-bot MCP 도구를 활용해 자동화한다. task-scheduler에 cron으로 등록하면 완전 자율 실행이 가능하다.
워크플로우 1: 모닝 브리핑
실행 시점: 평일 오전 9시 자동 실행 또는 "모닝 브리핑", "오늘 브리핑" 요청 시
Step 1 — 어제 요약 수집
memory_search:
category: "daily-logs"
limit: 1
→ 어제 날짜의 데일리 로그 조회
→ 주요 활동 3줄로 요약
Step 2 — 미완료 할일 수집
memory_search:
tag: "todo"
limit: 20
→ 결과를 importance 기준 내림차순 정렬
→ priority-high > priority-mid > priority-low 순서로 그룹핑
Step 3 — 오늘 예정 일정 수집
memory_search:
tag: "{오늘 날짜, 예: 2026-03-21}"
limit: 10
→ 미팅, 마감, 이벤트 등 시간순 정렬
Step 4 — 업계 뉴스 수집 (선택)
web_search:
query: "{사용자 관심 분야} 최신 뉴스"
→ Web3 보안, AI 에이전트, 스타트업 관련
→ 상위 3건만 한 줄 요약
→ 이 단계는 선택적이며, 네트워크 실패 시 건너뛴다
Step 5 — 브리핑 생성 & 전송
references/routine-templates.md의 모닝 브리핑 템플릿에 수집 데이터를 채운다.
messenger_send:
platform: "telegram"
message: "{생성된 브리핑 마크다운}"
브리핑을 데일리 로그에도 기록:
memory_daily_log:
entry: "모닝 브리핑 생성 및 전송 완료"
type: "note"
워크플로우 2: 할일 관리
할일 추가
사용자가 할일을 언급하면 아래와 같이 저장한다:
memory_store:
category: "tasks"
title: "{할일 제목}"
content: "{상세 설명 (있으면)}"
tags: ["todo", "priority-{high|mid|low}", "{프로젝트명}"]
importance: {high=9, mid=7, low=6}
저장 후 확인 기록:
memory_daily_log:
entry: "할일 추가: {할일 제목}"
type: "todo"
할일 완료 처리
memory_update:
id: {해당 메모리 ID}
mode: "metadata"
tags: ["done", ...기존 태그에서 "todo" 제거]
memory_daily_log:
entry: "{할일 제목} 완료"
type: "done"
할일 리뷰
"할일 정리", "오늘 할일" 요청 시 실행:
memory_search:
tag: "todo"
limit: 30
→ importance 내림차순 정렬
→ priority-high (🔴), priority-mid (🟡), priority-low (🟢) 아이콘으로 시각화
→ 기한 초과 항목은 ⚠️ 표시
워크플로우 3: 저녁 리뷰
실행 시점: 매일 21시 자동 실행 또는 "하루 마무리", "저녁 리뷰" 요청 시
Step 1 — 오늘 데일리 로그 조회
memory_search:
category: "daily-logs"
limit: 1
→ 오늘 날짜의 로그 전체 조회
Step 2 — 완료/미완료 분류
memory_search:
tag: "done"
category: "tasks"
limit: 20
→ 오늘 완료된 항목 수집
memory_search:
tag: "todo"
limit: 20
→ 아직 미완료인 항목 수집
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 285 lines · 96 tokens per session scan A d4b000fec092
daily-routine is a skill published in the GitHub repository Kit4Some/Oh-my-ClaudeClaw (4 stars, last pushed 5mo ago), licensed MIT. It adds 96 tokens to every session and 2,024 once invoked, about $0.0005 per session on Opus 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 skills, from other repositories
new
Start a new session — save summary to memory, then mark as reset so next message gets a fresh greeting. OpenClaw-compatible. Triggers on /new, /reset, /agent:new, "nueva sesión", "new session", "reset".
usage
Show usage cost summary — session, today, last 30 days. OpenClaw-compatible format. Works from CLI or messaging. Triggers on /usage, /agent:usage, "cuanto gasté", "agent usage", "cost".
assess
Issue triage and status assessment - analyze current state, detect health signals, and recommend next action with full workflow plan.
release
Automates the full release workflow: version bump, git tag, GitHub release, and npm publish.
solve
Deprecated: alias for /assess. Generate the recommended workflow for one or more GitHub issues.
reflect
Strategic reflection on workflow effectiveness and continuous improvement.