← Back to list

dsh-token-heatmap

DeepSeek Harness Other Low risk

GitHub-style daily token-usage heatmap on the new-session screen with a selectable calendar-year view, green/blue color schemes, and today / this-month / all-time totals.

新建会话页的 GitHub 风格每日 Token 用量热力图:可选日历年度视图、绿/蓝配色与显示开关,并附今日/本月/累计总量。

How to install

DeepSeek Harness dsh plugin add @kidli1412/dsh-token-heatmap

About

dsh-token-heatmap DSH Web GUI 插件:在**新会话(hero)屏幕的输入框下方**显示一个 GitHub 风格的 token 用量热力图 —— **当前自然年(1月–12月)**每天的 token 用量,颜色深浅表示用量多少;同一行展示**今日 / 本月 / 累计** token 用量。 A DeepSeek Harness web plugin: a GitHub-style daily token-usage heatmap of the **current calendar year (Jan–Dec)** rendered **below the composer input card on the new-session screen only**, with today / this-month / all-time totals on the same line. 界面 / What you get 新会话屏幕输入框正下方出现一张统计卡(**只在新会话显示**;已对话的会话不显示): 📊 **自然年热力图**:GitHub 风格,覆盖所选自然年 1月–12月(可切换年份,‹ 年份 › 选择器在统计行右侧,最多到当前年),列为周(周一起),行为星期(左侧标注一~日全部 7 天);顶部月份标签按列跨度标注(左侧与格线对齐),今日之后的日期显示…

Recommendation signals

59 Tool quality · Based on stars, downloads, maintenance, security and docs
– User interest · Adjusted by in-site views, install copies and download clicks
59 Overall
0views
0unique visitors
0install copies
0download clicks
0outbound clicks

Meta

License
MIT
Language
JavaScript
GitHub stars
1
mo. downloads
1.0K
Last push
2026-09-15
Created
2026-08-16

Links

Basic safety check

Findings
None
Sources
curated:awesome-dsh-plugin.com, curated:awesome-dsh-plugin/awesome-dsh-plugin
Topics
deepseek-harness, dsh-plugin, heatmap, token-usage

Related plugins

DeepSeek Harness
Score73

TokenLedger

zh667/TokenLedger

Sidebar usage panel that attributes tokens to the relay site that served each request, read from your existing provider config: today/month/all-time totals, per-site and per-model breakdowns, a year activity heatmap, and New API / Sub2API / DeepSeek balances.

☆ 202 ↓ 1.4K Other ↗
DeepSeek Harness
Score71

dsh-context

bowenliang123/dsh-context

DSH context insight panel: Context dashboard + /context command + Context browser — one-stop context lifecycle management with categorized composition, content details, evolution trends, compaction/injection events, and stats.

☆ 1.5K ↓ 79.7K Other ↗
DeepSeek Harness
Score69

dsh-usage-statistics-panel

HaoyueQin/dsh-usage-statistics-panel

Usage statistics settings panel: 26-week activity heatmap, daily token trend with a cache hit-rate curve, per-model donut and breakdown, time-range filters, summary cards, one-time historical backfill and lossless rebuild.

☆ 9 ↓ 3.3K Other ↗
DeepSeek Harness
Score68

dsh-all-usage

ParticleLight/dsh-all-usage

Analyze usage across models, providers, workspaces, and time ranges — including custom start/end dates over the full retained history — with live cache-hit visibility and separate model and provider breakdowns. Includes hourly single-day trends, daily cross-day trends, a 53-week GitHub-style heatmap, usage streaks, model and workspace Token-share donut charts with Token, cost, and percentage details, independent combinable filters, cache-efficiency trends, DeepSeek account balance, workspace aliases, CSV export, and a durable ledger that preserves successfully flushed usage after session deletion — and after a workspace is deleted, where its recorded usage is summed into one Deleted row — and rebuilds incrementally — on restart, unchanged sessions are applied from the ledger without re-reading their logs (a per-session log revision is the change signal), and only changed/new events are folded. The workspace registry is kept fresh automatically through the DSH domain/changed probe: only added/removed workspaces are reprocessed incrementally, unchanged workspaces reuse their computed aggregates and ledger with zero rescan, and usage is strictly limited to DSH-registered workspaces (unregistered cwds are ignored). After a scan, lightweight revision status fetches full history only when the Host/data state changes and exposes non-sensitive sync health (revision reuse, rereads, ledger recovery, and failures). Token accounting is explicit: input is fresh (cache read/write and reasoning are separate buckets) and zero-usage replays never overwrite recorded usage. Chinese uses local time, English uses UTC; API access is loopback-only.

☆ 8 ↓ 2.8K Other ↗