A comprehensive proactivity framework that enables AI agents to learn from feedback, prevent repetitive mistakes, and adapt to user preferences.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install aeon-proactivity
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install aeon-proactivity using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Aeon Proactivity?
Aeon Proactivity is an advanced behavioral layer designed for AI agents to transition from passive responders to active partners. By integrating this skill, agents gain the ability to observe conversation dynamics, recognize patterns in user feedback, and systematically log corrections to ensure continuous improvement. It transforms the interaction lifecycle by prioritizing user intent and long-term memory management.
Built with privacy and efficiency in mind, this skill manages local memory files to store successes, preferences, and configuration histories. It empowers Openclaw Skills to handle complex, multi-session tasks by providing context-aware summaries and proactive reminders, ensuring the agent evolves alongside the user's specific workflow requirements.
Aeon Proactivity Use Cases
- Automatically logging corrections when a user identifies an error to prevent future occurrences.
- Detecting repetitive command sequences to suggest automation scripts or shortcuts.
- Providing cross-session context summaries at the start of a new interaction to maintain continuity.
- Implementing high-risk action safeguards, such as requesting confirmation before deleting files or changing system configs.
- Tracking time-bound commitments and reminders based on natural language mentions.
How Aeon Proactivity Works
- The agent monitors user input for specific feedback triggers like 'wrong', 'incorrect', or expressions of frustration.
- Upon detecting a correction, the skill follows a three-step protocol: acknowledge the error, log the technical details to local storage, and verify the next attempt.
- The system scans local markdown files in the .learnings directory to apply previous success patterns and user preferences to current tasks.
- For high-risk operations, the skill intercepts the workflow to trigger a confirmation dialogue and suggest a backup.
- At the end of a session, the skill generates a summary of completed and remaining tasks, storing them for the next session initialization.
Aeon Proactivity Setup
To install and configure the Aeon Proactivity skill, ensure your environment has access to local storage and execute the following:
# Navigate to your agent's skill directory
cd ~/.openaeon/workspace/
# The skill utilizes the following local directory structure automatically
mkdir -p .learnings/{memory,preferences,history}
Ensure that the agent has localStorage.read and localStorage.write permissions enabled to allow the memory and learning protocols to function correctly within the Openclaw Skills environment.
Aeon Proactivity Data Schema & Taxonomy
The skill organizes data within ~/.openaeon/workspace/ using a structured taxonomy of Markdown files:
| File Path | Purpose | Key Metadata |
|---|---|---|
.learnings/LEARNINGS.md |
Core Lessons | Date, Error, Expected vs Actual, Correct Approach |
.learnings/ERRORS.md |
Mistake Tracking | Specific actions to avoid based on user feedback |
.learnings/SUCCESS_PATTERNS.md |
Best Practices | Task descriptions and effective methods |
.learnings/REMINDERS.md |
Task Queue | Description, Mention Date, Status (Pending/Done) |
.learnings/CONFIG_HISTORY.md |
System Changes | Change logs, timestamps, and reasoning |
Aeon Proactivity Advanced Features
- Emotion Detection: Dynamically adapts response tone and length based on user signals like terse responses or long explanations.
- Automation Discovery: Identifies batch processing opportunities when multiple similar tasks are detected.
- Memory Optimization: Includes a cleanup protocol to merge similar entries or summarize files exceeding 100KB.
- Skill Recommendation: Proactively suggests other relevant Openclaw Skills based on the current task context.
- Verification Protocol: Guides users through manual verification steps for system-level changes to ensure accuracy without requiring root execution.
SKILL.md
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