A powerful utility for extracting session insights, managing persistent memory, and retrieving historical dialogue contexts for AI agents.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install session-recall
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 session-recall 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 Session Traceback & Memory Management?
The Session Traceback Skill is a specialized toolset designed to give AI agents a long-term memory and the ability to audit past interactions. By leveraging this capability within Openclaw Skills, agents can move beyond ephemeral sessions to create a structured repository of knowledge based on their daily activities.
This skill enables the extraction of key decisions, todos, and user preferences into daily Markdown memory files. It also provides a robust mechanism for searching through historical logs stored in JSONL format, ensuring that no critical information is lost over time. This makes it an essential component for developers building sophisticated agents that require continuity and deep context awareness.
Session Traceback & Memory Management Use Cases
- Summarizing daily agent activities into persistent Markdown memory logs.
- Searching for specific keywords or historical contexts across hundreds of past sessions.
- Restoring previous conversation fragments to the current active session for continuity.
- Auditing agent decisions by reviewing reset or deleted session history files.
How Session Traceback & Memory Management Works
- The agent identifies the relevant session using the sessions_list tool to browse historical metadata.
- Detailed conversation logs are retrieved using sessions_history or by directly accessing the JSONL files in the agent storage path.
- The agent analyzes the retrieved data to find specific keywords, summaries, or context triggers.
- Extracted insights are either presented to the user or persisted into long-term storage using the write tool to update daily memory files.
Session Traceback & Memory Management Setup
To utilize this skill within the Openclaw Skills environment, ensure your agent has access to the standard session management tools. Use the following commands to interact with the history:
# List all sessions to find the target sessionKey
sessions_list
# Retrieve the full history of a specific session
sessions_history --sessionKey "agent:agent_id:platform:type:id"
# Read a specific session log file directly from the filesystem
read ~/.openclaw/agents/<agentId>/sessions/<sessionId>.jsonl
Session Traceback & Memory Management Data Schema & Taxonomy
The skill organizes session data and memory using a structured file hierarchy:
| Data Type | File Path / Pattern | Format |
|---|---|---|
| Session Index | ~/.openclaw/agents/<agentId>/sessions/sessions.json |
JSON |
| Conversation Logs | ~/.openclaw/agents/<agentId>/sessions/<sessionId>.jsonl |
JSONL |
| Daily Memory | memory/YYYY-MM-DD.md |
Markdown |
| Reset History | *.jsonl.reset.<timestamp> |
JSONL |
| Deleted History | *.jsonl.deleted.<timestamp> |
JSONL |
Session Traceback & Memory Management Advanced Features
- Direct JSONL parsing for high-performance keyword searching across large log volumes.
- Support for retrieving archived data from reset or deleted session files for disaster recovery.
- Automated extraction logic for daily summaries, including important decisions and pending todos.
- Integration with the Openclaw Skills toolset to bridge context between different agent platforms like Feishu or CLI.
SKILL.md
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