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dsh-tool-turbo

已验证 · 实测可装 Electricitysheep

✓ 持续维护 基于 3 个官方 DSH 包 纯 TypeScript

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TypeScript语言
2026-08-17最近推送
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功能简介

每轮 reasoning_effort 优化器。

✅
我们的评价
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:

  1. Watch the step's recent tool/call records from the session.
  2. Decide: simple, deterministic tools (write, read, grep, glob, bash, fs_*, …) with small payloads → low; mixed/heavy work → high; very heavy payloads → max (opt-in).
  3. Inject the decision into the agent/request config 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 to low, downgrades respect the user toggle, heavy payloads upgrade to max (opt-in), mixed tools lift to high.
  • tsc --noEmit clean.

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

🧩 让 Agent 自动装(推荐)

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。

安全:尚未扫描——我们的每日静态扫描将很快覆盖它。

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