apple-reminders
Manage Apple Reminders via the `remindctl` CLI on macOS (list, add, edit, complete, delete). Supports lists, date filters, and JSON/plain output.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Manage Apple Reminders via the `remindctl` CLI on macOS (list, add, edit, complete, delete). Supports lists, date filters, and JSON/plain output.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming. Use when you need to build complex AI systems, program LMs declaratively, optimize prompts automatically, create modular AI pipelines, or build RAG systems and agents.
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Real-time observability dashboard for multi-agent Claude Code sessions. Visualize agent interactions, tool usage, and session flows in real-time through a web dashboard. Track multiple agents running in parallel with swim lane visualization, event filtering, and live charts. **Key Features:** - 🔴 Real-time event streaming via WebSocket - 📊 Agent swim lanes showing parallel execution - 🔍 Event filtering by agent, session, event type - 📈 Live charts for tool usage patterns - 💾 Filesystem-based (no database required) **Inspired by [@indydevdan](https://github.com/indydevdan)**'s work on multi-agent observability. **Our approach:** Filesystem + in-memory streaming vs. indydevdan's SQLite database approach.
Track and optimize agent specialization during methodology development. Use when agent specialization emerges (generic agents show >5x performance gap), multi-experiment comparison needed, or methodology transferability analysis required. Captures agent set evolution (Aₙ tracking), meta-agent evolution (Mₙ tracking), specialization decisions (when/why to create specialized agents), and reusability assessment (universal vs domain-specific vs task-specific). Enables systematic cross-experiment learning and optimized M₀ evolution. 2-3 hours overhead per experiment.
Routes tasks to appropriate Task tool agents (subagents). Triggers on complex multi-step tasks, research, code review, exploration, or any task benefiting from specialized agent execution. Matches intent to agent types.
| name | apple-reminders |
| description | Manage Apple Reminders via the `remindctl` CLI on macOS (list, add, edit, complete, delete). Supports lists, date filters, and JSON/plain output. |
| homepage | https://github.com/steipete/remindctl |
| metadata | {"clawdbot":{"emoji":"⏰","os":["darwin"],"requires":{"bins":["remindctl"]},"install":[{"id":"brew","kind":"brew","formula":"steipete/tap/remindctl","bins":["remindctl"],"label":"Install remindctl via Homebrew"}]}} |
Use remindctl to manage Apple Reminders directly from the terminal. It supports list filtering, date-based views, and scripting output.
brew install steipete/tap/remindctlpnpm install && pnpm build (binary at ./bin/remindctl)remindctl statusremindctl authorizeremindctlremindctl todayremindctl tomorrowremindctl weekremindctl overdueremindctl upcomingremindctl completedremindctl allremindctl 2026-01-04remindctl listremindctl list Workremindctl list Projects --createremindctl list Work --rename Officeremindctl list Work --deleteremindctl add "Buy milk"remindctl add --title "Call mom" --list Personal --due tomorrowremindctl edit 1 --title "New title" --due 2026-01-04remindctl complete 1 2 3remindctl delete 4A83 --forceremindctl today --jsonremindctl today --plainremindctl today --quietAccepted by --due and date filters:
today, tomorrow, yesterdayYYYY-MM-DDYYYY-MM-DD HH:mm2026-01-04T12:34:56Z)