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dsh-mood

Fun & Dress-up Updated 2026.08.31

Run the following command in DeepSeek Harness:

dsh plugin install Raphaelutumn/dsh-mood

Paste the following prompt into your AI chat to install this plugin:

Run dsh plugin install Raphaelutumn/dsh-mood in DeepSeek Harness to install; the full source is at https://github.com/Raphaelutumn/dsh-mood .

About this plugin

AI coding agents move fast and get stuck just as fast. Consecutive failures, the same tool called over and over, a spike in activity — these signals are buried in the log, and your only option is to scroll back and guess whether it is still on track. dsh-mood collapses those signals into four emoji lights in the session header, so you can tell at a glance whether your agent is doing fine, spinning, visibly frustrated, or fully overwhelmed.

Under the hood it is an interpretable behavior classification, not magic. Every Mood is backed by a fixed, verifiable reason: three consecutive failures trigger Frustrated, repeating one tool past a threshold triggers Confused, and only high activity plus failure plus repetition together escalate to Overwhelmed. Upgrades are sensitive, recovery is conservative — bad news lights up immediately, but returning to Good takes a few steady successes, preventing the mood from flickering on every alternation. All signals are computed locally, nothing leaves the machine, no prompt is injected, no tool call is vetoed. It is a pure read-only observer.

It is for DeepSeek Harness users who want an at-a-glance pulse on their agent without opening a dashboard or parsing logs. Every threshold is tunable via profile config, and the full surface — host and client — is backed by 32 tests.

Screenshots

Use Cases

  • Agent fails repeatedly and you want to spot the stall without scrolling through logs
  • Need a quick pulse on whether the agent is progressing or spinning in circles
  • Add a fun, zero-setup status light to your daily coding session without a dashboard

Best For

  • Daily DeepSeek Harness coding-agent users
  • Developers who prefer a glance over a full monitoring dashboard
  • Engineering teams that value interpretable and verifiable behavior signals