A specialized tool for auditing AI memory layers to ensure context clarity and promote durable project instructions.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install memory-landscape-review
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 memory-landscape-review 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 Landscape Review?
Memory Landscape Review is a powerful utility designed for users of Openclaw Skills to maintain high-quality AI context. It systematically analyzes transient auto-memory and permanent project files to bridge the gap between temporary session data and durable instructions. By providing a unified view of repository-wide, personal, and team-wide memory, this skill ensures that your AI agent always operates with the most accurate and relevant project knowledge.
This skill is particularly valuable for complex projects where multiple instructions might overlap or conflict over time. It helps developers maintain clean project documentation by identifying which patterns in auto-memory have become stable enough to be codified into permanent rules, thus optimizing the performance and reliability of Openclaw Skills.
Memory Landscape Review Use Cases
- Converting frequent auto-memory snippets into permanent repo-wide guidelines.
- Finding and eliminating contradictory instructions across different memory layers.
- Distinguishing between personal developer preferences and shared project standards.
- Periodic auditing of project context to reduce token usage and improve agent accuracy.
How Memory Landscape Review Works
- The skill aggregates data from repository memory files, local personal memory, and the current auto-memory state.
- Each piece of information is classified into categories such as repo-wide, personal, or temporary.
- The system performs a conflict and duplicate detection pass to highlight inefficiencies.
- A detailed report is presented to the user, categorizing potential promotions and cleanups.
- Changes are only applied to the underlying files once the user provides explicit approval for the proposed plan.
Memory Landscape Review Setup
To utilize this skill within your Openclaw Skills ecosystem, ensure the memory review component is active in your configuration. You can trigger the review process through standard natural language commands via your AI agent.
# The skill is typically available as a bundled command
openclaw run memory_landscape_review
Ensure you have a CLAUDE.md or similar memory file in your repository root to serve as the destination for durable instructions.
Memory Landscape Review Data Schema & Taxonomy
| Feature | Description |
|---|---|
| Memory Layers | Analyzes auto-memory, CLAUDE.md, and local memory files. |
| Classification | Metadata tags for shared, personal, team, or temporary scope. |
| Proposal Report | A grouped list of recommended promotions and deletions. |
| Change Log | Records of approved modifications to durable memory files. |
Memory Landscape Review Advanced Features
- Multi-layer analysis covering repo, personal, and session-specific context.
- Intelligent promotion logic that targets specific files like CLAUDE.md for durable storage.
- Safety-first guardrails that prevent any silent or automated editing of documentation.
- Conflict resolution strategies to handle overlapping instructions across Openclaw Skills.
SKILL.md
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