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Install in OpenClaw
/install remind
Description
Auto-learns when and how to bring things back to your human's attention. Adapts timing and style to their preferences.
Usage Guidance
This skill is instruction-only and appears coherent for a reminder assistant. Before installing, confirm two things with the skill author or your platform: (1) what data sources the skill will 'observe' to learn (conversation history, calendar, email, notifications, etc.), and whether you must grant any connectors; and (2) where learned preferences and reminders are stored and how you can review or delete them. If you are concerned about autonomous learning, run it with model invocation limited or in a restricted test environment until you verify its behavior. If you plan to integrate it with calendars or email, only grant the minimum connector access required.
Capability Analysis
Type: OpenClaw Skill
Name: remind
Version: 1.0.0
The OpenClaw skill 'Remind' is designed to help users remember commitments and events. Its core loop involves detecting remindable items, evaluating preferences, delivering reminders, observing user reactions, and storing learned preferences for timing and style. All instructions across `SKILL.md`, `timing.md`, and `triggers.md` are consistent with this stated purpose, focusing on adaptive reminder management. There is no evidence of prompt injection attempting to subvert the agent, exfiltrate data, execute unauthorized commands, or perform any other malicious actions. The learning mechanism is described in a way that aligns with a benign, adaptive assistant feature.
Capability Assessment
Purpose & Capability
Name and description match the instructions: detect known commitments, decide timing/style, remind, observe reactions, and update preferences. No unexpected binaries, credentials, or installs are requested that would contradict a reminder assistant.
Instruction Scope
SKILL.md, timing.md, and triggers.md stay on topic (detect remindable items, lead times, triggers). However the skill repeatedly says it will 'observe' user reactions and 'auto-learn' without specifying the data sources (conversation history, calendar, email, notifications) or the mechanism for observation. That vagueness means the agent could rely on any conversational context it has access to — reasonable, but worth clarifying before trusting autonomous learning.
Install Mechanism
Instruction-only skill with no install spec or code files. Lowest-risk install profile: nothing is downloaded or written by the skill itself.
Credentials
No environment variables, no credentials, and no required config paths are declared. The requested permissions are proportionate to a reminder assistant. Note: actual operation may require connectors (calendar, email, notification channels) in practice — those are not declared here.
Persistence & Privilege
always is false and model invocation is allowed (normal). The skill says it will 'Store — Update preferences below' but does not specify where preferences are persisted (agent memory, user storage, external service). Ask how and where learned preferences are saved and how to clear them.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install remind - After installation, invoke the skill by name or use
/remind - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release
Metadata
Frequently Asked Questions
What is Remind?
Auto-learns when and how to bring things back to your human's attention. Adapts timing and style to their preferences. It is an AI Agent Skill for Claude Code / OpenClaw, with 2759 downloads so far.
How do I install Remind?
Run "/install remind" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Remind free?
Yes, Remind is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Remind support?
Remind is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Remind?
It is built and maintained by Iván (@ivangdavila); the current version is v1.0.0.
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