dsh-fixed-new-session-model
Run the following command in DeepSeek Harness:
dsh plugin install chenyangcun/dsh-fixed-new-session-model
Paste the following prompt into your AI chat to install this plugin:
Run dsh plugin install chenyangcun/dsh-fixed-new-session-model to install; source is available at https://github.com/chenyangcun/dsh-fixed-new-session-model
About this plugin
Juggling multiple workspaces in DeepSeek Harness often means re-picking an Agent preset and model on every new session, with in-conversation switches quietly overriding whatever you intended. dsh-fixed-new-session-model pins those defaults as persistent configuration so that a single pass in Settings → Default Mode & Model is all you ever need to set up consistent, predictable sessions.
The plugin builds on a three-tier inheritance model: a global default layer defines the Agent preset, provider, model ID, and reasoning level; a workspace layer can override either field independently—for example, locking one project to standard-codex while its model still follows the global choice; and a blank-session layer auto-applies the matching rules when a session is created or recycled, while already-active conversations are left untouched. Everything rides on DSH’s native settings system with no extra database or credential files, and the built-in settings page lets you edit, inspect, or revert workspace rules in one click.
If you maintain several workspaces, have a stable preference for specific Agent presets or models, or are tired of inconsistent outputs caused by drifting model selections, this plugin makes defaults predictable and per-project differences reusable—so you can spend less time configuring and more time producing.
Screenshots
Use Cases
- Pinning different Agent presets and models per project across multiple workspaces
- Enforcing a uniform model version to prevent output drift from in-session switches
- Auto-inheriting preset and model on new blank sessions without manual selection each time
Best For
- DSH users maintaining multiple workspaces with distinct configuration needs
- Developers with stable preset and model preferences who require consistent outputs
- Teams preferring native settings-page management without extra configuration tooling
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