Weidows/dsh-performance-optimizer

dsh-performance-optimizer

DSH bundle that exposes host-wide performance metrics (CPU / memory / IO) via a Settings tab, an optional HUD, and a native agent tool.

待分类deepseek-harnessdiagnosticsperformance

dsh-performance-optimizer

DSH bundle that exposes host-wide and per-event-loop performance metrics so the user (via a Settings tab) and the agent (via a native tool and a stdio MCP server) can reason about scroll lag, memory drift, and tool loops.

The bundle is intentionally minimal — it samples Node process.memoryUsage() / process.cpuUsage() once per second, keeps a 60-sample rolling buffer, and exposes it through three surfaces:

surface · consumer · mechanism Settings → Plugins tab · user · client.js mounts ` into the per-plugin detail page; live table + Canvas2D chart with CPU / RSS / Heap / Wall tabs. Floating HUD · user (opt-in) · client.js mounts into the document body when hudVisible: true. Native tool · agent (in-session) · ctx.tools.register('performance_report')` returns a fresh JSON report on demand.

Files

file · role index.js · Host half. Owns the sampler, the performanceOptimizer Cordis service, and the performance_report tool. client.js · Web GUI half. Two custom elements (`, ); routes by ctx.slot. Calls back into the Host via the runtime bridge. cordis.patch.yml · Loader patch: one insert — the bundle itself. locale/en.json · English copy. locale/zh.json · 简体/中文 copy. icon.svg` · Bundle icon.

Install

# from npm
npx @deepseek-ai/dsh plugin --profile web add dsh-performance-optimizer

# from source
npx @deepseek-ai/dsh plugin --profile web add github:Weidows/dsh-performance-optimizer

# from a local clone
npx @deepseek-ai/dsh plugin --profile web add /absolute/path/to/dsh-performance-optimizer

Restart the Web profile and open .

npx @deepseek-ai/dsh web

To remove:

npx @deepseek-ai/dsh plugin --profile web remove dsh-performance-optimizer

What it measures

sample field · source · what it answers t / tHr · Date.now() + process.hrtime.bigint() · When was this sample taken (clock / monotonic, never trust the wall for ordering). rss · process.memoryUsage().rss · Has the Host process grown? Did release/manual GC help? heapUsed · process.memoryUsage().heapUsed · V8 heap pressure (RSS includes native). heapTotal · process.memoryUsage().heapTotal · Did V8 grow the heap (hint of churn). external · process.memoryUsage().external · Native buffers / modules. cpuMs · process.cpuUsage() · Cumulative user/system CPU time (ms). cpuDeltaMs · delta against previous sample · CPU burn between two ticks; correlates with sampler tick & loop work. wallDeltaMs · now - lastCpu.takenAt · Sampler timer drift — catches stalled timers caused by event-loop saturation. uptimeMs · process.uptime() * 1000 · Host uptime.

History is the last historySize samples (default 60). Sampling interval is sampleIntervalMs (default 1000 ms). When MCP is enabled, the most recent report is also written to a JSON file under the bundle's plugin directory every tick so the stdio MCP server can read it without holding a reference into the Host process.

How it talks to DSH

The Host half uses only Cordis accessors declared in inject:

  • tools — registers performance_report. Every MCP tool call routed through DSH eventually surfaces through tools.register, so this is the canonical agent interface regardless of whether @deepseek-ai/dsh-mcp-client is also mounted.
  • pluginContext — composition helper; lets the patch layer attach additional reads.

The Client half is mounted once per dsh.client.inject target. The package.json lists three:

  • @deepseek-ai/dsh-client-ui-settings-plugins — registers the per-plugin detail tab. This is the canonical user surface.
  • @deepseek-ai/dsh-client-shell — registers the HUD.
  • @deepseek-ai/dsh-client-ui-conversation — reserved for a future chip; currently no-op.

It looks up the runtime bridge via window.__DSH_HOST__ / window.__DSH__ / window.deepseek.host (whichever is present) and calls plugin:performance-optimizer.snapshot | .history | .config | .sample | .reset. If the bridge is missing, the tab renders an empty state and the HUD shows — — neither blocks the rest of the UI.

Tool surface (native)

{
  "name": "performance_report",
  "arguments": {},
  "result": {
    "kind": "json",
    "value": {
      "intervalMs": 1000,
      "sampleCount": 42,
      "latest": { "t": "2026-10-20T11:39:42.000Z", "rss": 314572800, "heapUsed": 134217728, "cpuMs": { "user": 1234.5, "system": 67.8 }, "...": "..." },
      "history": [ /* last 10 samples */ ],
      "generatedAt": "2026-10-20T11:39:42.000Z"
    }
  }
}

Agent surface

The bundle exposes one native tool:

performance_report

It returns the same JSON-shaped report shown above. Every MCP tool call routed through DSH ultimately surfaces through ctx.tools.register, so this is the canonical agent interface — there is no separate MCP server in this bundle.

If you want external MCP clients (Claude Code, Codex, an inspector) to also pull snapshots, write a small sibling DSH plugin that mounts an MCP server and reads ctx.performanceOptimizer.buildReport() for each tool call. Keeping MCP server concerns out of this bundle avoids coupling to a specific @modelcontextprotocol/sdk version.

Config

sampleIntervalMs: 1000  # sampling cadence in milliseconds
historySize: 60         # rolling buffer length
hudVisible: false       # boot-time HUD visibility
settingsTab: true       # mount the Settings → Plugins detail tab

All keys are optional; defaults are baked into the bundle.

Failure / uninstall

When the bundle is disabled in the Plugins page, ctx.effect cleanups tear down:

  • the sampler timer on the Host,
  • the performance_report tool registration,
  • the HUD element,
  • the `` element.

No side effects on the Host process remain.

License

MIT — see LICENSE.