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bowenliang123 /

dsh-context

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A DeepSeek Harness plugin for Context dashboard and command — showing what the model's context window is made of and how it evolves.

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dsh-context

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A DeepSeek Harness plugin for context dashboard and context command, for understanding how the context is made of, and how it evolves.

dsh-context is a DeepSeek Harness plugin for context insight.

  • The Context tab — a full insight panel for context composition, per-turn context history, context compactions, and the message surface, etc.
  • The /context command — the same headline and recent trend as a centered dialog straight from the composer (the screenshot above).

Install

One command, from any DeepSeek Harness installation:

dsh plugin --profile web add dsh-context

Then start the web UI with dsh web. No build step, no restart.

Use it

Context tab

Open any session and click the Context / 上下文 tab:

Context panel overview

⌨️ /context command — In-session Context Insight modal

Type /context (or pick it from the / menu) and press Enter: a centered dialog shows the provider-anchored occupancy headline, the six-category composition bar, and the last-10-turn trend chart — hover or click a bar for its full breakdown, exactly like the tab.

Context command

What you'll see

📊 Context stats — the session at a glance

Turns, steps, how much context has been recycled by compactions and prunes, how many injections happened, model switches, and the estimated total tokens sent — next to the provider-reported actuals, so you can see how the estimate holds up.

🧱 Current composition — what's in the window right now

A six-color stacked bar scaled against the model's full context window (the gray track is your remaining headroom): system prompt, tool schemas, your messages, injected context, assistant replies, and tool results — plus the top-5 most expensive tool schemas. When a conversation starts degrading, this is where you find out which part ate the budget.

📈 History — watch the window grow (and get compacted)

One stacked bar per model request, finer than per-message. Toggle between Turn and Step granularity, scroll sideways through the session, hover any bar for a quick tooltip, and click to pin the full breakdown — including provider-reported actual prompt/output tokens next to the estimate. ✂ marks where compaction or pruning happened — watch the bars drop:

History chart with a pinned request

Above: a real session that grew to ~563k tokens across 48 turns, then compaction (✂) recycled −535.5k in one step, and the conversation continued from a fresh, small window.

In Step granularity, hovering any bar shows that single step's context info instantly — its turn/step, timestamp, and estimated vs. provider-reported token counts:

History chart with a step hover tooltip

⚡ Context events — when and why the window changed

Every compaction, tool-output prune, skill or plugin context injection, and model switch — each with its token delta, turn/step attribution, and timestamp:

Context events and messages

💬 Messages — the currently model-visible surface

The exact message list the model sees right now, newest first, with a per-message token cost.

Like it?

If dsh-context helped you understand what your agent is carrying around, a ⭐ on GitHub is much appreciated — and issues/PRs are welcome!

License

Apache-2.0

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