A sophisticated utility for OpenClaw that injects time-based freshness warnings into memory search results to ensure AI agents validate outdated information.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install openclaw-memory-freshness
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 openclaw-memory-freshness 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 OpenClaw Memory Freshness?
OpenClaw Memory Freshness is designed to solve a specific limitation in the OpenClaw 4.2 memory system: the lack of modification timestamps in search results. Without these timestamps, an AI model cannot distinguish between a memory created yesterday and one created six months ago, leading to potential hallucinations or the use of deprecated code.
By integrating this tool into your collection of Openclaw Skills, you provide the agent with the context needed to evaluate data reliability. It implements a tiered warning system that ranges from low-priority suggestions to high-priority mandates for verification, ensuring that the AI always works with the most accurate project state.
OpenClaw Memory Freshness Use Cases
- Identifying stale project configurations that may have changed since the last memory was recorded.
- Forcing the AI to verify the existence of functions or files using grep when memory age exceeds 7 days.
- Enhancing long-term project maintenance by flagging architectural decisions that are over 30 days old for re-validation.
- Reducing errors in multi-agent workflows where different agents might rely on legacy memory entries.
How OpenClaw Memory Freshness Works
- The skill monitors memory search results and identifies the age of retrieved entries based on their modification metadata.
- It assigns a freshness level (Fresh, Low, Medium, or High) based on a defined timeline: <=1 day, 2-7 days, 7-30 days, or >30 days.
- A specific warning string or icon is injected into the search result metadata provided to the LLM.
- The system prompt directs the agent to perform specific validation actions, such as using ripgrep or reading file contents, before acting on the memory if it is deemed outdated.
OpenClaw Memory Freshness Setup
To configure OpenClaw Memory Freshness, you can use the recommended system prompt injection method. Update your configuration file at ~/.openclaw/openclaw.json by adding the following to the agents.defaults.systemPrompt section:
## Memory Freshness Rules
1. <= 2 days: Use information directly.
2. 2–7 days: Simple validation (e.g., check if the file still exists).
3. 7–30 days: Mandatory validation (e.g., grep for function signatures or match content).
4. > 30 days: Mark as potentially obsolete; must read the actual file before proceeding.
OpenClaw Memory Freshness Data Schema & Taxonomy
The skill structures freshness data using the following taxonomy within search results:
| Property | Description | Example Value |
|---|---|---|
| Age | Days since memory creation | 7 days ago |
| Level | Severity of the freshness warning | ⚠️ Medium |
| Action | Required validation step | grep -n [keyword] |
| Timestamp | Exact date of entry | 2026-03-01 |
OpenClaw Memory Freshness Advanced Features
- Tiered freshness logic with distinct warnings for low, medium, and high-risk data.
- Automated validation hooks that trigger shell commands like grep and rg for real-time verification.
- Support for manual bypass when users explicitly authorize the use of legacy memory.
- Flexible implementation options including system prompt injection or memory file header modification.
SKILL.md
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