@Saccc_c: In Deepseek Harness's trajectory mode, you can also view its system prompt (see Figure 1). I translated it into Chinese; interested friends can take a look (see Figures 2 and 3)
Summary
The tweet introduces Deepseek Harness's trajectory mode, which allows viewing the Agent's thinking steps, tool calls, and system prompts, accompanied by a Chinese translation for easy learning.
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In Deepseek Harness’s trace mode, you can also view its system prompt (see Figure 1)
I translated it into Chinese; friends who are interested can take a look (see Figures 2 and 3) https://t.co/OcdmwYDdLe
Sac (@Saccc_c): Deepseek harness’s trace mode is so interesting. Now you can fully know how your Agent is progressing. Your Agent employees won’t dare slack off anymore 😂
Its specific thinking steps, tool calls, and tool return results are all clearly visible. The most interesting part is that it uses different colors to distinguish AI
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@Saccc_c: Deepseek harness's trace mode is so interesting, now you can completely know the progress of Agent's work, and your Agent employees will never dare to slack off again. Its specific thinking steps, tool calls, and tool return results are all clearly visible. The most interesting thing is that it uses different colors to distinguish when AI executes tasks…
DeepSeek Harness has been released, featuring a trace mode that visualizes Agent's thinking steps, tool calls, and return results, and uses colors to distinguish different types of content. It can be installed via npm and is suitable for developers to observe Agent work progress.
@seekjourney: Everyone may have missed a hidden treasure in DeepSeek Harness's release yesterday: .agents/skills/ directly contains 11 real engineering Skills: Code Review, Pre-push Checks, finding over-engineering, Stacked…
Introduces the .agents/skills/ directory included in the DeepSeek Harness release, containing 11 real engineering Skills (such as code review, pre-push checks, CoT leakage cleanup, etc.), which is equivalent to open-sourcing part of their engineering standards and Agent SOP.
@tianyi: If you are a developer of an open-source project related to Agent Harness and wish to participate in the beta testing of DeepSeek Harness, you can reply or message me privately. Please include your GitHub ID and representative open-source works.
A DeepSeek team member invites developers of open-source projects related to Agent Harness to participate in the beta testing of DeepSeek Harness, with a GitHub ID and representative works required.
@Saccc_c: L站 netizens are still too impressive. Someone reverse-engineered part of the technical architecture based on the leaked DeepSeek Harness closed-beta ecosystem plugin repository on GitHub, for reference. All I can say is I'm looking forward to DeepSeek Harness!
L站 netizens reverse-engineered part of the technical architecture based on the leaked DeepSeek Harness closed-beta ecosystem plugin repository on GitHub, sparking anticipation for DeepSeek Harness.
@jakevin7: https://x.com/jakevin7/status/2086031167040426488
Maka is an open-source Agent Harness. Through mechanisms such as log-as-runtime, context pruning, and thinking feedback, it cuts the cost of the same DeepSeek task to 1/8 of OpenCode, while achieving a higher pass rate on Terminal-Bench at lower cost.