deepseekplugins

DeepSeek Harness plugin

dsh-token-stats-18412203

DSH plugin: token usage & cost statistics per model / date / session with history backfill and CSV/JSON export

Memory
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Source facts

Repository
1841220388zzzcccxxx-star/dsh-token-stats
Latest update
Aug 22, 2026
Category
Memory
GitHub stars
2
Format
plugin
Catalog evidence
Upstream dsh.bundle evidence
Evidence path
package.json#dsh.bundle
Checked against
0.1.0-rc.8
Upstream check date
2026-08-20

This evidence comes from the upstream catalog. This site has not installed, run, or security-reviewed the plugin.

Install

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Do not install or run any commands yet. Read this plugin's GitHub repository, README, and relevant source code. Then answer the questions below clearly and directly so I can decide whether it fits my needs:

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GitHub: https://github.com/1841220388zzzcccxxx-star/dsh-token-stats
Plugin: dsh-token-stats-18412203
Author: 1841220388zzzcccxxx-star

Check the source files

Read the README and other files from this plugin directory before installing.

File explorer4 files
README.mdSource · read only
README language

dsh-token-stats

Token usage & cost statistics plugin for DeepSeek Harness (DSH).

Tracks token consumption per model, per date, and per session with cost estimation in USD / CNY, served as a native page under Settings → 📊 Token Stats. Installed as an external DSH plugin, it loads automatically at DSH startup — no manual activation needed.

中文说明

Features

  • 📊 Native settings page (dark/light aware, follows DSH theme tokens, i18n zh/en)
  • 📈 Daily / weekly / monthly trends with an SVG line chart (zero dependencies)
  • 💰 Cost estimation (USD & CNY) from a built-in pricing table for DeepSeek, GPT, Claude, Gemini, Qwen…
  • 🔁 History backfill: scans all persisted session logs at startup, so stats survive restarts
  • ⚡ Fast: batched session-title reads with an in-memory cache (TTL 5 min), single-pass summaries, memoized pricing
  • 📤 CSV / JSON export, filterable by model and session

Screenshot

![Token Stats dashboard](docs/demo.png)

Installation

The plugin is installed as an external DSH profile dependency.

1. Clone / copy this repository to a local folder, e.g. D:\dev\dsh-token-stats 2. In your DSH profile manifest (~/.dsh/profiles/web/package.json):

``jsonc { "dependencies": { "dsh-token-stats": "file:D:/dev/dsh-token-stats" }, "dsh": { "profile": { "bundles": ["@deepseek-ai/dsh-base", "@deepseek-ai/dsh-web-app", "dsh-token-stats"] } } } ``

3. cd ~/.dsh/profiles/web && pnpm install 4. Restart DSH web. Open Settings → 📊 Token Stats.

> cordis.patch.yml declares the bundle-layer mount point so the plugin auto-loads at startup.

How it works

  • Authoritative data = DSH persisted session logs: assistant/message events carry real usage

(input / output / cache-read / cache-write / reasoning tokens), request/header events carry provider/model.

  • A one-shot backfill at startup (sessionQuery) rebuilds the in-memory aggregation index from all history

(bounded concurrency).

  • llm/stream usage chunks are captured for live (display-only) in-flight totals.
  • When an adapter reports no usage, tokenMeter.estimateMessage is used and the record is flagged estimated.

HTTP API (/token-stats/api)

| op | description | | --- | --- | | summary | today / week / month / total aggregates | | query | time series (day/week/month) + per-model / per-session aggregates; filters: model, sessionId, from, to | | models | built-in pricing table (USD per 1M tokens) + USD→CNY rate | | sessions | session list (id + title) | | export | CSV / JSON dump (format=csv\|json, optional model / sessionId) |

Development

node --check index.js      # server half
node --check client.js     # browser half
node test-plugin.js        # standalone mock tests: correctness + performance benchmarks
.\sync-deploy.ps1          # re-sync sources into the DSH profile (then restart DSH web)

Performance

Measured on the author's machine (14 sessions / ~10k records):

endpointbeforeafter
sessions~1700 ms (N serial readTitle calls)~12 ms (one batched readTitleSnapshots + cache)
summary~110 ms (4× full-array filters)<1 ms (single pass)
query~10 ms~18 ms at 10k records (memoized cost)

License

[MIT](./LICENSE) © 2026 quansheng

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