hierarchical-memory

What This Skill Does

The Hierarchical Memory skill transforms how an AI agent handles long-term context by implementing a neural branching structure. Instead of relying on a flat, monolithic log that quickly exceeds context windows, this skill organizes data into a tiered architecture: Root, Domain, and Project. By segregating information, the agent can perform 'surgical' reads—loading only the specific project file or domain knowledge required for a task. This drastically reduces context bloat and increases the accuracy of model responses. The skill includes a robust helper utility, add_branch.py, which automates the tedious aspects of file creation, folder structure management, and bidirectional linking, ensuring your memory ecosystem remains consistent and navigable.

Installation

To integrate this memory management system, execute the following command in your terminal: clawhub install openclaw/skills/skills/balkanblbn/hierarchical-memory Once installed, verify that the memory/ directory has been initialized in your project root. The scripts/add_branch.py script will be available to help you scaffold new knowledge layers.

Use Cases

• Complex Project Management: Keep track of intricate project specifications, to-do lists, and technical histories without letting them clutter your primary context.
• Knowledge Siloing: Separate distinct areas of operation (e.g., trading, coding, and social research) to ensure that the agent remains focused on the relevant philosophy and parameters for the task at hand.
• Long-term Context Retention: Prevent 'context drift' by forcing the inclusion of a 'Significance' note in every entry, ensuring that only high-value data persists over time.

Example Prompts

1. "Initialize a new project branch for 'Project-X' under the 'Coding' domain and link it to the root memory map."
2. "Read the recent_delta.md file in the 'Trading' domain and summarize the critical updates from the last 5 days."
3. "Search my root memory for the 'Research' domain index, then retrieve the primary architectural goals defined in the project file for 'BalkanBot'."

Tips & Limitations

• Atomic Writes: Ensure your project files are strictly scoped to one initiative to avoid retrieval errors.
• Significance Tracking: Every new entry must define its significance to prevent the accumulation of 'Zombie Memory'—useless data that drains processing power.
• Maintenance: Regularly review your recent_delta.md files during agent heartbeats to reconcile state changes.
• Limitation: This system requires active management. While the helper scripts automate the scaffolding, the human or agent must be disciplined in maintaining the backlink structure to avoid orphaned files.