dsh-where-did-my-tokens-go
DSH 插件：深度思考指示器后的实时 token 计数器
插件会安装到这里；不确定时保持 web。
npx -y @deepseek-ai/dsh plugin --profile web add github:RevxZxCx/dsh-where-did-my-tokens-go#fd1f0d48bdadf726ae5988aaf2b33c26b7f64d8c
Where Did My Tokens Go 以 dsh-where-did-my-tokens-go 发布，当前版本为 1.6.2。Plugin Hub 会校验它的 manifest，并保存精确安装来源，便于复现安装结果。
Realtime token badges beside the deep-thinking indicator — merged or split in/out, a think/answer split of the output, auto K/M/G/T units, per-step operation counts
Where Did My Tokens Go? is a community-maintained DeepSeek Harness (DSH) plugin, not an official DeepSeek AI product.
This README describes 1.6.2.
Put "where did this turn's tokens go" directly in the transcript: a live counter rides the deep-thinking indicator, and every finished operation row is tagged with the cost of its own step. The plugin is global — once installed, every conversation gets it.
in N = input tokens, out N = output tokens, think N = the reasoning share of the output.contextPressure), so it is live during the input phase without waiting for provider usage; once the provider reports inputTokens, that authoritative value takes precedence; before either exists, the last known input is reused. Output counts are estimated client-side while streaming (CJK glyph ≈ 1 token, latin ≈ 4 chars/token) and snap to the authoritative value when the stream settles.reasoningTokens breaks the output figure into what the model spent thinking and what it spent writing. think N is that reasoning share — it is part of out, never an extra term, so out = think + answer and the visible answer is simply out − think. While the model is still thinking, the reasoning text is the whole output stream, so the merged badge labels the running number think; once the answer starts (or the step settles) the total appears with its think share beside it, and split mode shows in … · out … · think …. The provider's reasoningTokens is authoritative when reported; otherwise the share is estimated from the reasoning stream and clamped to the output total, so it can never exceed the figure it belongs to. A model that streams no reasoning text shows exactly the same badge as before — there is simply no share to print — which is why this is safe to leave on.1866 → 1.9K, 2 500 000 → 2.5M; below 1000 the raw number shows; a rounding that would print 1000K promotes to 1M instead. A gear menu can also lock one unit for a site, which then always scales by it.in … during the input phase, then think … while the model is reasoning, then out … (with its think share) while generating; split shows in … · out … · think … together for the whole turn.use N token: every completed operation row (「已完成思考」, 「已完成命令」, …) gets a use N token label styled like that row, showing its own step's tokens (input + output, or the provider's totalTokens when it reports one) — never the whole reply's total.The live badge beside the deep-thinking indicator (split mode):
Each finished operation row tagged with its own step cost:
The settings page with preview cards and switches:
Screenshots are taken from the 1.6.0 release running on DeepSeek Harness 0.2.0-rc.2; UI crops keep only the relevant panels, saved as lossless WebP.
Requires a working DeepSeek Harness installation. The commands below use the desktop profile; replace it with yours if needed.
Send this to an agent that can operate your terminal:
Install the dsh-where-did-my-tokens-go plugin from npm into my DSH profile, verify it is served after the install, and tell me how to reload.
dsh plugin --profile desktop add dsh-where-did-my-tokens-go
dsh plugin --profile desktop add github:RevxZxCx/dsh-where-did-my-tokens-go
# 1. pack the plugin
cd packages/dsh-where-did-my-tokens-go
pnpm pack
# 2. install into the desktop profile
dsh plugin --profile desktop add ./dsh-where-did-my-tokens-go-<version>.tgz
# (or manually: add the tarball to the profile's package.json dependencies and
# append "dsh-where-did-my-tokens-go" to dsh.profile.bundles, then `pnpm install`)
# 3. restart DSH
After installing, restart DSH and open any conversation — the badge appears once you send a message. Re-run the install command to update.
1.6.2 is tested running on DeepSeek Harness 0.2.0-rc.2 (desktop profile, Windows).| What you want | How |
|---|---|
| Watch this turn's in / out tokens | Send a message and read the badge after the 「深度思考」 indicator; it counts in real time. |
| See how much of the output was thinking | Keep the think switch on: think N is the reasoning share inside out N, so the written answer is out − think. |
| Switch merged / split | Open Settings → Token 计数器 and click the matching preview card. |
| Keep only in or only out | Toggle the other switch off — both preview cards drop the segment immediately. |
| See what each finished operation cost | Keep the use switch on; every 「已完成…」 row gets its own number. |
| Make big numbers readable | Leave units on auto, or lock K / M / G / T for a site in its gear menu. |
| Restyle one site | Gear → font size / color / unit. 0 and "follow theme" mean no override. |
| Check before saving | Gear edits reflect in the preview cards right away; the chat badge only changes when you press save. |
K on an extreme number never prints 1000K; it keeps promoting upward (capped at 1000T).think is a share, not a term: it comes from the provider's reasoningTokens, which the platform validates to be <= outputTokens. Adding out + think double-counts; the answer is out − think. When the provider reports no reasoningTokens, the share is estimated from the reasoning stream and clamped to out; a model that streams no reasoning text shows no think segment at all.sessions service and the active (main-view) session's binding.eventSource.text-delta / reasoning-delta stream chunks as they arrive (the reasoning text feeds both the output total and its own breakdown), reads the live input count from the harness's contextPressure projection, and records authoritative usage per step from the usage chunk / assistant/message event (keyed by turn + step), including reasoningTokens.configForms.lib/index.js — host half: schemastery Config + apply.lib/client.js — browser half via window.__ModuleLoader__.load.cordis.patch.yml — registers the plugin profile entry.package.json — dsh.bundle + dsh.client = { platform: "web", inject: [...] }.node test/run-tests.mjs # mocked-browser unit tests (~480 assertions, covers every feature)
node test/probe-served.mjs # checks the running DSH serves the current on-disk client build
Issues and suggestions are welcome on GitHub Issues — please include your DSH and plugin versions and steps to reproduce; full screenshots help for UI problems. If the settings form reports "This plugin is not loaded, so it cannot be configured right now", the host half is not mounted — run dsh --profile desktop --dump-config (or check the profile's cordis.patch.yml) before filing an issue.