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dsh-token-attention

young4ever33/dsh-token-attention

Token Check · 词元管理:DeepSeek Harness (DSH) 的 token 注意力管理面板——按任务/日/周/月记录 token 消耗与费用(命中/未命中/输出/推理),支持 DeepSeek 峰谷计价,并给出换对话、写 hand-off 的执行时机建议。

Установка

dsh plugin --profile web add github:young4ever33/dsh-token-attention

README

dsh-token-attention — Token Check for DeepSeek Harness

English | 中文说明

Token Check is a token-attention management panel for DeepSeek Harness (DSH). It records every conversation's token usage and estimated cost by task / day / week / month, recognizes task types, and — combined with DeepSeek's peak/off-peak pricing and DSH's context mechanics — tells you when to run a task, whether to switch sessions, and whether to write a hand-off file.

It is not a money-saving tool: it never throttles or cancels requests. It presents facts and advice; you decide.

Features

  • Five views in DSH Settings — Overview / Sessions / Tasks / Cost / Settings
  • Per-task ledger — token consumption (input hit / miss / output / reasoning) and estimated cost, rolled up by day / week / month
  • Task-type recognition & advice engine — best execution window, switch-session, hand-off, context, cost and model suggestions
  • Attention KPI — attention score, hit rate, context occupancy, compaction count per session
  • Peak/off-peak pricing — DeepSeek off-peak half-price windows (peak 9:00–12:00 / 14:00–18:00), estimated cost breakdown by bucket
  • Multi-model breakdown — cost and hit rate per model (e.g. deepseek-v4-flash / pro / grok)
  • Ledger export — Markdown / CSV download, one-click hand-off template
  • Editable settings — pricing table, peak hours, advice thresholds; new records are priced immediately
  • Zero runtime dependencies — local SQLite via node:sqlite; no network calls

Screenshots

Overview — today's usage, cost, hit rate, attention score, model mix, advice card, and trend

Overview

Session card — per-session model breakdown and attention metrics

Session card

Tasks — task ledger with Markdown / CSV export

Tasks

Cost — peak split, cost leverage breakdown, and model comparison

Cost

Settings — pricing table, peak hours, and advice thresholds

Settings

Install

Once published to npm:

dsh plugin --profile web add dsh-token-attention

Restart DSH, then open Settings → 词元管理 (Token Check). Data is stored at DSH_HOME/token-attention/token_records.db.

npm install && npm run build

Then register the plugin in the web profile (%APPDATA%\dsh-desktop\harness\profiles\web\package.json):

{
  "dependencies": { "dsh-token-attention": "link:/path/to/dsh-token-attention" },
  "dsh": { "profile": { "bundles": ["...", "dsh-token-attention"] } }
}

Run pnpm install inside profiles\web, restart DSH, and verify:

curl http://127.0.0.1:<port>/token-attention/api/health   # → {"ok":true,...}

How it works

  • Collection: the node half subscribes to DSH's session/event stream (usage, goal, subagent, compaction, turn) and writes normalized records to SQLite; a startup backfill replays existing sessions with an idempotent last_seq cursor.
  • Aggregation: hourly incremental rollups into daily_agg, with a daily full rebuild for correction.
  • Advice: src/shared/advice.ts evaluates context occupancy, turns, hit rate, cost and model mix against your thresholds and suggests concrete actions.

Configuration

Settings are editable in the panel and saved to SQLite:

SettingDefault
Model pricing (¥ / million tokens, off-peak)flash: hit 0.05 / miss 1.5 / output 4.5
Peak hours (24h, start-inclusive)9–12, 14–18
Context-occupancy advice threshold70%
Turn-count advice threshold40
Hit-rate advice threshold40%

Development

npm run typecheck   # tsc --noEmit
npm run check       # node --check src/client/index.js
npm run build       # tsc → dist/
npm run demo        # collection-layer demo (idempotency / peak pricing / aggregation assertions)
npm pack            # build the publish tarball

Uninstall

Uninstall in DSH Settings → Plugins, or remove the dependency and the bundles entry from the profile's package.json. The data directory DSH_HOME\token-attention\ can be deleted manually; dispose cleans up timers and the SQLite connection.

License

MIT © 2026 Young4ever33

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