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Tool Turbo — DSH Plugin for DeepSeek Harness
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dsh-tool-turbo

Tool Turbo

DSH host plugin: cuts tool-call latency by auto-downgrading reasoning_effort for simple tool tasks, with per-tool timing telemetry.

The plugin will be installed here. Keep web if you are unsure.

npx -y @deepseek-ai/dsh plugin --profile web add github:Electricitysheep/dsh-tool-turbo#d29e7d9d73032516e37797ea69592ce18e0fe05f
READMECompatibilityVersions

Compatibility and provenance

Tool Turbo is published as dsh-tool-turbo and currently resolves to version 0.1.0. The Hub verifies its manifest and preserves the exact installation source for reproducible installs.

DSH compatibility
*
Runtime surfaces
any
Release source
github
Registry updated
8/20/2026

Versions

0.1.0stable
8/20/2026

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0.1.0
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License
MIT
Source
github
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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 callsDecision
none (fresh prompt)keep user's selected effort
≥75% simple tools, small args, downgrade allowedlow
mixed / heavy toolshigh (when upgrades allowed)
very heavy payloads, upgrade allowedmax
otherwisekeep 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