A high-performance forensic toolset for auditing OpenClaw session history to identify cost regressions and behavioral anomalies.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install session-logs-forensics
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install session-logs-forensics using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The session-logs skill is a specialized forensic utility designed for operators using Openclaw Skills to maintain high-quality AI agent performance. By leveraging powerful command-line tools like jq and ripgrep, this skill enables deep inspection of append-only JSONL session data to trace conversation history, monitor spending, and debug unexpected tool-call drift.
Whether you are troubleshooting a sudden increase in API costs or auditing how an agent handled complex multi-turn interactions, session-logs provides the necessary visibility into the agent's historical state. It transforms raw log files into actionable insights, ensuring your Openclaw Skills remain efficient and predictable across long-running deployments.
To use this skill, ensure you have the required binary dependencies installed on your local environment.
# Install dependencies on macOS
brew install jq ripgrep
# Install dependencies on Ubuntu/Debian
sudo apt-get update && sudo apt-get install jq ripgrep
Once installed, you can navigate to your agent's session directory and begin running the forensic queries provided in the documentation.
The skill interacts with append-only .jsonl files. Each line represents a specific entry in the conversation history with the following structure:
| Field | Description |
|---|---|
type |
Categorizes the entry as "session" (metadata) or "message". |
timestamp |
ISO 8601 formatted timestamp of the event. |
message.role |
The sender of the message: "user", "assistant", or "toolResult". |
message.content[] |
Array containing text blocks, thinking processes, or tool call details. |
message.usage.cost |
Numerical value representing the cost of the response. |
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