插件目录 / Developer / dsh-tool-turbo
dsh-tool-turbo
已验证 · 实测可装 Electricitysheep
功能简介
每轮 reasoning_effort 优化器。
可用 — 实测通过,早期项目
每轮 reasoning_effort 优化器。 实测能干净安装、正常启动。早期项目,但功能可用。
「已验证」表示我们的自动化 CI 在干净 profile 里实际执行了 dsh plugin add 并启动成功——仅此而已。功能描述与版本兼容性均为作者声明。这不是安全审计,也不代表对第三方代码的背书。
README
dsh-tool-turbo
Cut tool-call latency in DeepSeek Harness (dsh) by auto-adjusting reasoning_effort per tool round.
中文文档 · English
In a multi-step tool chain, the model re-thinks before every tool call — and that thinking dominates the wall-clock time (a 50-step agent task can spend minutes in reasoning between tools). dsh-tool-turbo watches the recent tool calls of a step and injects the lowest sensible reasoning effort into the next model request, then lifts it again the moment the work gets heavy.
How it works
DeepSeek's API exposes reasoning_effort in three steps (low / high / max, shipped 2026-08-13). dsh re-resolves the request config for every step through an agent/request waterfall (see packages/core/agent-loop/src/agent.ts — "plugins propose the next request config"). dsh-tool-turbo plugs into that waterfall:
- Watch the step's recent
tool/callrecords from the session. - Decide: simple, deterministic tools (
write,read,grep,glob,bash,fs_*, …) with small payloads →low; mixed/heavy work →high; very heavy payloads →max(opt-in). - Inject the decision into the
agent/requestconfig for the next model call of that step.
Long tool chains keep the cheap rounds cheap, and never starve the hard rounds of reasoning.
Install
# 1. clone + build the plugin
git clone https://github.com/Electricitysheep/dsh-tool-turbo.git
cd dsh-tool-turbo && npm install
# 2. register into your dsh profile (web shown; any profile works)
# ~/.dsh/profiles/web/package.json dependencies:
# "dsh-tool-turbo": "link:<absolute path to dsh-tool-turbo>"
# ~/.dsh/profiles/web/cordis.patch.yml:
# - insert:
# - id: tool-turbo
# name: dsh-tool-turbo
cd ~/.dsh/profiles/web && pnpm install
# 3. restart dsh web
dsh web
Verified
- Injector works in a live dsh instance (log lines from a real run):
[tool-turbo] agent/request: baseline=high calls=[] => reasoningEffort=high
[tool-turbo] agent/request: baseline=high calls=[{"name":"write",…}] => reasoningEffort=low
- 6/6 unit tests on the effort policy (
decideEffort): fresh prompt keeps the baseline, simple-tool chains downgrade tolow, downgrades respect the user toggle, heavy payloads upgrade tomax(opt-in), mixed tools lift tohigh. tsc --noEmitclean.
Policy (pure, testable)
| Recent tool calls | Decision |
|---|---|
| none (fresh prompt) | keep user's selected effort |
| ≥75% simple tools, small args, downgrade allowed | low |
| mixed / heavy tools | high (when upgrades allowed) |
| very heavy payloads, upgrade allowed | max |
| otherwise | keep user's selected effort |
Toggles (settings namespace planned): allowDowngrade (default on), allowUpgrade (default off — keep max conservative), baseline (default high).
Roadmap
- effort-decision core + waterfall injection
- per-tool duration telemetry (host log)
- settings namespace (dsh-settings) for the toggles
- tool timing surfaced in the UI / agent context
- profile-agnostic install docs (
headless/tui)
License
MIT
安装
装一次目录插件,之后本站所有插件都能让 DeepSeek Harness 自动找、自动装:
dsh plugin add dshbase-catalog 然后对 agent 说「帮我装 dsh-tool-turbo」,它会在目录里找到并自动安装。文档:dshbase-catalog · 已验证场景包。
该插件是 GitHub 源码(未发 npm)——直接从仓库装:
Web profile:
dsh plugin --profile web add github:Electricitysheep/dsh-tool-turbo Headless(CLI)profile:
dsh plugin --profile headless add github:Electricitysheep/dsh-tool-turbo 实测报告
验证通过:从 GitHub 源码完成 L1 安装 + L2 加载 + L3 运行(dsh 0.1.0-rc.6)。
使用场景
扩展 agent 的编码能力面——给它一个新工具、工作流或集成,让它接手以前做不了的开发任务。
适合谁
想让 dsh 在真实代码库上像队友一样干活的开发者——能改、能跑、能验证,而不只是回答问题。
二次开发建议
工具/命令面就是缝:暴露更多 SDK 能力、加更聪明的上下文接线,或收紧改代码与验证之间的循环。