Memory Auto-Index for Openclaw

An automated indexing skill that synchronizes memory files and tracks key decisions for AI agents.

mengnessly
v1.0.0
Apr 16, 2026
0
760
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install memory-auto-index

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install memory-auto-index 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 Memory Auto-Index?

The Memory Auto-Index skill is designed to bridge the gap between raw memory logs and a searchable knowledge base. Within the Openclaw Skills framework, this tool automatically maintains the relationship between the central MEMORY.md index and individual files stored in the memory directory. It ensures that every piece of recorded information is categorized and easily retrievable.

By leveraging automated tag extraction and deduplication logic, it provides developers with a structured way to manage long-term agent context. This is particularly valuable for complex projects where tracking architectural decisions, user preferences, and troubleshooting history is critical for consistent AI performance.

Memory Auto-Index Use Cases

  • Automatically organizing daily AI memory logs into a centralized index.
  • Tracking high-level architectural and project decisions across multiple development sessions.
  • Categorizing user preferences and interaction history using a standardized tag system.
  • Maintaining a clean and searchable MEMORY.md file without manual intervention.
  • Troubleshooting agent behavior by quickly locating specific error logs and fix records.

How Memory Auto-Index Works

  1. The process begins when a user instruction or system event triggers a new entry in a memory log file.
  2. The skill extracts relevant tags and subjects from the content based on predefined mapping rules or explicit user annotations.
  3. The auto-index-memory.sh script is invoked, either manually or via an automated trigger in the code.
  4. The script calculates the exact line numbers or section anchors for the new content within the memory file.
  5. It performs a deduplication check to ensure the index remains clean and organized.
  6. The central MEMORY.md file is updated with new references under subject-based, project-based, or decision-based headers.

Memory Auto-Index Setup

To get started with this skill in your Openclaw Skills environment, ensure the scripts have the necessary execution permissions.

chmod +x scripts/auto-index-memory.sh

You can manually index a file using the following command structure:

./scripts/auto-index-memory.sh <file_path> <subject> <tag_list>

Memory Auto-Index Data Schema & Taxonomy

The skill organizes data using a hierarchical taxonomy and a central index file. This structure ensures that Openclaw Skills can quickly traverse the memory directory.

Component Path Description
Main Index MEMORY.md The central entry point for all indexed memory, organized by tags and decisions.
Memory Logs memory/YYYY-MM-DD.md Daily logs containing raw context and events.
Logic Script scripts/auto-index-memory.sh The shell script responsible for parsing and updating the index.
Metadata AGENTS.md Documentation regarding the memory writing workflow and agent protocols.

Memory Auto-Index Advanced Features

  • Multi-criteria indexing: Sorts entries by subject, project, and critical decisions simultaneously.
  • Semantic search readiness: Optional scripts available to generate JSON indexes for vector-based search.
  • Automatic categorization: Dynamically creates topic-specific files when a certain tag threshold is reached.
  • Validation tools: Built-in maintenance scripts to check for invalid references or broken file links within the Openclaw Skills repository.
  • Anchor-based linking: Support for linking to specific section headers to maintain link integrity even if line numbers change.

SKILL.md


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