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dsh-novel-solo

DeepSeek Harness 的「单核写作」插件:面向量化小模型做了充分的工具瘦身与输出加固,适合在本机用本地模型跑长篇小说流水线。

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Language
JavaScript
Created
Aug 27, 2026
Updated
Aug 27, 2026
GitHub repo

Introduction

dsh-novel-solo

A single-author novel-writing plugin for DeepSeek Harness: a subagent concurrency setting plus a complete novel-creation preset (persona). It is tuned for quantized small models — the tool catalog is slimmed and output behavior hardened — so you can run a full-length novel pipeline locally.

Features

  • GUI setting: adds a "Subagent count (1-12)" selector under Settings → General, with built-in zh/en i18n.
  • Full creation preset: ships the novel-solo preset with a self-driven persona that follows a fixed pipeline — 叙事方法 (narrative method) → 核心世界观 (core worldview) → 名词索引 (noun index) → 大纲 (outline) → 章节目录 (chapter list) → 人物档案 (character files) → chapter-by-chapter writing → per-chapter review → final whole-book review & assembly.
  • Quantized-safe protocol: plain CJK + common punctuation only, no JSON, no escapes, avoids fragile tokens; minimal tool calls, one at a time.
  • Review loop: every chapter is reviewed (green/yellow/red) across 7 dimensions (setting / character / catalog / narrative / text rules / AI-cliché / plot logic); each report is written to a markdown file; when all chapters pass, a whole-book review runs and the book is assembled.
  • No AI clichés: ships shared writing/review blacklists for structural tics, expression tics, emotion tics, repetition, and lazy connectors.
  • Slimmed catalog: hard-disables whole tool rows (shell / jobs / skills / goals / web) inside the preset to shrink the tool schema.
  • Versioned writing: each chapter is 第N章-章节名字-vX.md; full-chapter rewrites first copy to v(X+1) and never overwrite older drafts.

Install

dsh plugin --profile web add "dsh-novel-solo"
dsh web

Then open Settings → General; the "Subagent count" row appears at the bottom.

On first launch the plugin idempotently deploys the preset from template/ to <dshHome>/.agent-presets/novel-solo/ (skips if the target already exists — it never overwrites your edited preset).

How the subagent count takes effect

DSH's agent/request waterfall only lets a plugin rewrite LLM routing/config — it cannot inject or rewrite system/messages — so "GUI → model prompt" dynamic injection cannot go through the request waterfall. This plugin uses a two-stage wiring instead:

  1. On save, N is written to ~/.dsh/.dsh-novel-solo-data/agent-count.json (the single source of truth).
  2. The persona's sync anchor 并发上限 N=<number> is rewritten in place (by default in the deployed preset ~/.dsh/.agent-presets/novel-solo/agent.cordis.yml). The persona then decides: N=1 the main agent does everything itself; N>1 writing/review tasks are delegated to subagents while the main agent only dispatches and silently waits.

Note: the persona is loaded each time a preset session starts. A GUI change edits files, so running sessions pick up the new N only after a restart / new session.

Preset at a glance

template/agent.cordis.yml (deployed to ~/.dsh/.agent-presets/novel-solo/agent.cordis.yml) includes:

SectionContent
Division of laborconcurrency anchor N=1 (default), with N=1 / N>1 execution paths
Quantized-safe rulestop-priority constraints on output and tool calls
Six-doc standard structuresper-field templates for 叙事方法 / 核心世界观 / 名词索引 / 大纲 / 章节目录 / 人物档案
Writing & review ruleschapter rules, AI-cliché lists, A–G review dimensions + green/yellow/red, md review reports, whole-book review & assembly
Tool usage standardsper-tool rules for read/write/edit/glob/grep/subagent, etc.
Project & disciplineproject dir {{cwd}}/项目名/, one thing at a time, etc.

Tool slimming

The preset hard-disables these rows via disabled: true: tool-bash, tool-pwsh, tool-jobs, skill-filesystem, tool-skill, tool-goal, plan-mode, subagent_codex, subagent_claude_code, workflow-worker-thread, tool-workflow, tool-ralph, tool-ask-user, tool-todo, tool-web. It keeps tool-fs (read/write/edit), tool-fs-search (glob/grep), subagent/subagent_fork, list_agents, etc.

It also ships a preset-scoped vendored plugin (active only for sessions mounting the novel-solo preset):

  • template/plugins/llm-tool-choice-pin/index.mjs — pins toolChoice to auto for the llama provider so retained tools like edit stay callable (avoids per-request tool decisions under small models).

File structure

lib/index.js        node half: RPC channel /dsh-novel-solo (read / writeAgentCount), file store, preset deploy
lib/client.js       browser half: registers settings.general.item (id agent-count), renders the 1-12 selector
cordis.patch.yml    inserted into the web profile on install
template/           the novel-solo preset (agent.cordis.yml + vendored plugin), shipped with the package
package.json        dsh.client metadata so the plugin is recognizable by the plugin market/manifest

Environment variables

VariablePurposeDefault
DSH_HOMEdsh home directory~/.dsh
DSH_NOVEL_PERSONA_YAMLtarget YAML for the concurrency-anchor rewrite (can point to any preset)<dshHome>/.agent-presets/novel-solo/agent.cordis.yml
DSH_NOVEL_PERSONA_MDextra persona md file to also sync (optional)none
DSH_NOVEL_SKIP_DEPLOY1 skips preset deploymentnone
DSH_NOVEL_REDEPLOY1 forcibly overwrites an existing preset (use with care)none

Test environment

This plugin was tested end-to-end with a local model:

  • Runtime: llama.cpp (llama-b10615-bin-win-cuda-13.3-x64)
  • Model: Qwen3.6-35B-A3B-Uncensored-HauhauCS-Aggressive-IQ4_XS.gguf
  • Context: ctx=65536, reasoning on
  • Hardware: laptop RTX 4060 8GB + 32GB RAM + AMD 7840H CPU
  • Measured on a ~10k-char novel: 22 token/s, 98% cache hit; 78.8k input / 36.9k output / 2.3M cache; 22 turns / 63 steps, 1h03m42s total

Key server flags (llama-server):

llama-server.exe -m <model.gguf> --no-mmproj --load-mode none --n-cpu-moe 30 -c 65536 -ngl 999 -t 12 -b 1024 -ub 512 -ctk q8_0 -ctv q8_0 -fa on --fit off --no-warmup --poll 0 --temp 0.85 --top-k 20 --top-p 0.95 --min-p 0.05 --repeat-penalty 1.35 --presence-penalty 0.2 --frequency-penalty 0.2 --dry-multiplier 0.8 --dry-base 1.75 --jinja --reasoning on --reasoning-effort medium --reasoning-budget 2048 --reasoning-format deepseek --reasoning-preserve --cont-batching -np 1 --alias "qwen3.6-novel-nsfw-reason" --port 8090 --host 127.0.0.1 --ui --keep -1 --cache-ram 4096 --ctx-checkpoints 64

License

MIT License

Copyright (c) 2026 Tkingxiao

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.