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 agentmods add skills/starrycod/cogitum/apple-remindersnpx skills add StarryCod/cogitum --skill apple-remindersgit clone --depth 1 https://github.com/StarryCod/cogitumWrote 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/starrycod/cogitum/apple-reminders)<a href="https://agentmods.dev/skills/starrycod/cogitum/apple-reminders"><img src="https://agentmods.dev/badge/skills/starrycod/cogitum/apple-reminders.svg" alt="Measured on agentmods" 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 | $0.00017 | $0.00684 |
| Opus 5 | $0.00009 | $0.00342 |
| Sonnet 5 | $0.00003 | $0.00137 |
| Haiku 4.5 | $0.00002 | $0.00068 |
Grade A, and why
apple-reminders 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 4d 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.
This is a copy
88% identical to apple-reminders — 17 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Requires macOS
Apple Reminders
Use remindctl to manage Apple Reminders directly from the terminal. Tasks sync across all Apple devices via iCloud.
Prerequisites
- macOS with Reminders.app
- Install:
brew install steipete/tap/remindctl - Grant Reminders permission when prompted
- Check:
remindctl status/ Request:remindctl authorize
When to Use
- User mentions "reminder" or "Reminders app"
- Creating personal to-dos with due dates that sync to iOS
- Managing Apple Reminders lists
- User wants tasks to appear on their iPhone/iPad
When NOT to Use
- Scheduling agent alerts → use the cronjob tool instead
- Calendar events → use Apple Calendar or Google Calendar
- Project task management → use GitHub Issues, Notion, etc.
- If user says "remind me" but means an agent alert → clarify first
Quick Reference
View Reminders
remindctl # Today's reminders
remindctl today # Today
remindctl tomorrow # Tomorrow
remindctl week # This week
remindctl overdue # Past due
remindctl all # Everything
remindctl 2026-01-04 # Specific date
Manage Lists
remindctl list # List all lists
remindctl list Work # Show specific list
remindctl list Projects --create # Create list
remindctl list Work --delete # Delete list
Create Reminders
remindctl add "Buy milk"
remindctl add --title "Call mom" --list Personal --due tomorrow
remindctl add --title "Meeting prep" --due "2026-02-15 09:00"
Complete / Delete
remindctl complete 1 2 3 # Complete by ID
remindctl delete 4A83 --force # Delete by ID
Output Formats
remindctl today --json # JSON for scripting
remindctl today --plain # TSV format
remindctl today --quiet # Counts only
Date Formats
Accepted by --due and date filters:
today,tomorrow,yesterdayYYYY-MM-DDYYYY-MM-DD HH:mm- ISO 8601 (
2026-01-04T12:34:56Z)
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.
- 4d ago First seen · 102 lines · 17 tokens per session scan A 74051d9d1b36
apple-reminders is a skill published in the GitHub repository StarryCod/cogitum (11 stars, last pushed 3mo ago), licensed MIT. It adds 17 tokens to every session and 684 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to apple-reminders, differing in 17 lines, and is treated as a copy.
Other skills, from other repositories
文档协作
引导用户通过结构化的文档共同编写工作流程。当用户想撰写文档、提案、技术规范、决策文档或类似结构化内容时使用。该工作流程帮助用户高效传递上下文，通过迭代优化内容，并验证文档对读者有效。当用户提到写文档、创建提案、起草规范或类似文档任务时触发。.
openmaic-classroom
将 RAG 检索结果、文档块或知识图谱概念转换为 OpenMAIC 互动课程。当用户要求将知识库内容、检索到的文档片段、上传的文档、或知识图谱中的概念批量转换为教学课件/互动课堂时使用此技能。支持纯需求生成、基于 PDF 内容的课程生成、和基于概念图遍历的批量课堂生成。.
weknora-shared
Use when driving a WeKnora RAG server through the weknora CLI as an agent — authenticating, managing knowledge bases / documents / sessions / agents, running search or chat, or interpreting the CLI's JSON envelopes and exit codes. Read this before any other weknora- skill.
weknora-rag-search
Use when retrieving from or asking questions against a WeKnora knowledge base via the weknora CLI — and especially when unsure whether to use chat, session ask, or search chunks for a given goal.
数据处理器
数据处理与分析技能。当用户需要对知识库检索结果进行数据分析、统计计算、格式转换、数据提取或生成报告时使用此技能。支持 Python 脚本执行进行高级数据处理。.
引用生成器
自动生成规范引用格式。当用户需要生成参考文献、引用来源、标注知识库内容出处、或要求提供引用信息时使用此技能。.