dsh-seelog
Run the following command in DeepSeek Harness:
dsh plugin install lhwu1/dsh-seelog
Paste the following prompt into your AI chat to install this plugin:
To install this plugin in DeepSeek Harness, run the command dsh plugin install lhwu1/dsh-seelog. The full source code address is https://github.com/lhwu1/dsh-seelog.
About this plugin
When using DeepSeek Harness for complex sessions, Session Logs can be overwhelming with raw JSON data, making it difficult to visualize the execution flow, especially in multi-agent interaction scenarios. The dsh-seelog plugin addresses this by transforming Session Logs into an interactive 3D session execution map, turning data into a visual and browsable format.
At its core, the plugin excels in smart mapping and interactive design. The main agent thread is displayed as a central line, with sub-agents forking off from their actual creation points and merging back at completion, all on a unified timeline for easy tracking of parent-child relationships and execution order. The interface features a fixed time overview ruler for quick navigation, a node inspector for detailed log inspection on click, and on-demand data loading to avoid performance issues from real-time polling. Additionally, it includes Chinese semantic mapping to translate tool calls and events into readable labels.
This plugin is ideal for developers and debugging personnel who need to visually analyze session flows, pinpoint issues, or understand agent interaction logic. For any DeepSeek Harness user, it significantly enhances the efficiency and experience of session analysis, making debugging and learning processes more intuitive and convenient.
Screenshots
Use Cases
- Debugging complex session flows during multi-agent interactions.
- Analyzing Session Logs to pinpoint execution errors or performance bottlenecks.
- Visually demonstrating AI agent workflows in teaching or presentations.
Best For
- Developers needing to visually analyze session data.
- Engineers debugging DeepSeek Harness applications.
- Students and tech enthusiasts studying or researching AI agent behavior.
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