A comprehensive infrastructure audit toolkit for validating pgvector configurations and ensuring knowledge graph integrity.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install firm-memory-audit-pack
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 firm-memory-audit-pack 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 Firm Memory Audit Pack?
The Firm Memory Audit Pack is a specialized suite of tools designed to maintain the health and reliability of AI memory systems. It provides deep inspection capabilities for pgvector databases and knowledge graphs, ensuring that the underlying data structures supporting your AI agents are optimized and error-free. By integrating these Openclaw Skills into your workflow, you can prevent common retrieval issues caused by misconfigured vector dimensions or broken graph connectivity.
This pack is essential for developers managing complex RAG (Retrieval-Augmented Generation) pipelines where data consistency is paramount. It bridges the gap between raw database management and high-level agent logic by providing automated validation of indices, distance metrics, and node relationships.
Firm Memory Audit Pack Use Cases
- Validating pgvector configuration settings including dimensions and distance metrics during environment setup.
- Detecting orphan nodes and broken links within complex knowledge graph structures.
- Identifying cycles in graph-based memory that could cause logic errors in agent traversals.
- Verifying index types (HNSW, IVFFlat) to ensure optimal search performance for Openclaw Skills.
- Performing routine infrastructure health checks after data migrations or system updates.
How Firm Memory Audit Pack Works
- The skill interfaces with your existing memory configuration via a standard JSON path.
- The pgvector audit tool executes a validation sequence to check for dimensional alignment and index efficiency.
- The knowledge graph audit tool performs a structural analysis to map connectivity and identify logical inconsistencies.
- Detailed audit results are generated, providing actionable feedback on infrastructure health.
- Developers can then use these reports to remediate configuration drift or data corruption.
Firm Memory Audit Pack Setup
To get started with these Openclaw Skills, ensure you have the required dependencies installed and the skill added to your environment:
# Install the necessary extension framework
pip install mcp-openclaw-extensions>=3.0.0
# Register the memory audit pack
openclaw skills add firm-memory-audit-pack
Firm Memory Audit Pack Data Schema & Taxonomy
The skill processes configuration files and generates detailed audit reports based on the following schema:
| Attribute | Description |
|---|---|
| pgvector_config | Validates dimensions, index_type, and distance_metric (L2, Cosine, etc.) |
| graph_integrity | Analyzes node connectivity, orphan detection, and cycle paths |
| audit_report | A structured output summarizing errors, warnings, and optimization suggestions |
Firm Memory Audit Pack Advanced Features
- Multi-metric distance validation for specialized semantic search requirements.
- High-performance cycle detection for large-scale enterprise knowledge graphs.
- Automated configuration validation for pgvector dimensions to prevent runtime mismatch errors.
- Seamless integration with other Openclaw Skills for automated memory maintenance workflows.
SKILL.md
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