dsh-cost-display
Run the following command in DeepSeek Harness:
dsh plugin install misakimiku2/dsh-cost-display
Paste the following prompt into your AI chat to install this plugin:
Run dsh plugin install misakimiku2/dsh-cost-display to install, or fetch the source from https://github.com/misakimiku2/dsh-cost-display and manually configure the profile.
About this plugin
You have been running models in DeepSeek Harness for hours, token counters climbing steadily, yet you have no idea what the session is actually costing. dsh-cost-display closes that gap by appending a real-time cumulative cost (Cost ¥X.XX) right after the token stats in the status bar. Hovering over it reveals a per-model breakdown that also separates reasoning tokens, so every dollar spent is transparently accounted for.
The pricing engine goes well beyond a flat rate. Peak and off-peak windows—defaulting to 09:00–12:00 and 14:00–18:00 Beijing time—let the plugin automatically select the correct tier at request time. Each model supports multiple price tiers with effective dates, so an official rate change is simply a new row in the table, no code edits required. When you add or rename a model in the settings page, the plugin syncs it into the price table on its own; unlisted models fall back to a safety rate marked with a ? prefix, and per-model peak pricing can be toggled off individually.
If you rely on DeepSeek for long-form writing, code generation, or heavy reasoning tasks and want a quiet, always-updating cost tracker beside your work without breaking your flow—or if you batch jobs during off-peak hours to cut unit prices—this lightweight plugin gives you a clear, real-time, and fully configurable picture of what you are actually spending.
Use Cases
- Monitor cumulative costs in real time during long-running inference sessions
- Schedule batch jobs during off-peak hours to reduce per-token expenses
- Update the price table after an official rate change and let the new tier take effect automatically
Best For
- Developers and researchers who call DeepSeek models at high frequency
- Teams that need to control API usage and stay within budget
- Individual users who want a transparent, always-visible cost breakdown
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