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dsh-novel-writer

by siweina
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JavaScript
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novel_sentence_config

View or update sentence-pattern analysis and writing-assistant switches: enable/disable features, auto-analyze, prompt mode/scene, and lean workflow to control analysis behavior.

Instructions

查看或修改句式模式分析的开关状态：enabled（分析功能是否可用）、autoAnalyze（分析作品时是否主动使用）、systemPromptMode（系统提示词档位 off/brief/full）、promptScene（提示词场景 general/writing/revising/auditing/setup，决定完整档下注入哪一套流程）与 leanWorkflow（精简工作流：打开后只按需调用工具，省 token）。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolsNo各工具开关（如 { novel_plot: false }），键必须是 novel_* 工具名。
actionNoget=查看；set=修改。
enabledNo写作助手功能总开关。
featuresNo功能开关（emotionCaveat=情感净化预警 / genreTheme=题材与流派检测 / webnovelVibe=网文信号 / rawWriting=非净化直白模式 / semanticEmbedding=本地语义增强），如 { emotionCaveat: false }。注意：rawWriting=true 会跳过 UI 的双重确认+承诺输入流程，仅应在用户明确要求时开启。
autoAnalyzeNo分析作品时是否主动使用句式分析。
promptSceneNo提示词场景（仅 full 档生效）：general=通用写作工作流（默认，等价于 4.x 行为） / writing=写新章 / revising=改稿 / auditing=审计（只体检不改稿） / setup=建资料（只维护设定与创作资料）。
leanWorkflowNo精简工作流（默认 false）：true=注入最简提示词（优先于档位与场景），只保留「工具按需调用」一条原则，报告类工具未显式传 brief 时默认走精简输出。适合成本敏感的长篇。
styleToleranceNo风格基线容差（每维 { low: -20, high: 20 }，low 为负/高为正；空对象 {} 清除恢复推荐——宿主不支持 null 类型，清除一律用空对象）。
creationProfileNo原创模式设定（worldview/characters/forbidden/mainConflict/genre/extra 字符串键，留空项省略；空对象 {} 清除全部交给模型——宿主不支持 null 类型）。
creationProfilesNo按书专属原创设定（键=书名，值=同上结构；空对象 {} 清除全部书的专属设定——宿主不支持 null 类型）。
systemPromptModeNo系统提示词档位：off=不注入 / brief=精简（只说明有这套工具） / full=完整（按场景注入对应流程）。

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv5.1.1
    • addedInput schema / properties / leanWorkflow
      Added value: +{
+  "description": "精简工作流（默认 false）：true=注入最简提示词（优先于档位与场景），只保留「工具按需调用」一条原则，报告类工具未显式传 brief 时默认走精简输出。适合成本敏感的长篇。",
+  "type": "boolean"
+}
  2. Changed2 schema fields changedv5.0.0
    • addedInput schema / properties / promptScene
      Added value: +{
+  "description": "提示词场景（仅 full 档生效）：general=通用写作工作流（默认，等价于 4.x 行为） / writing=写新章 / revising=改稿 / auditing=审计（只体检不改稿） / setup=建资料（只维护设定与创作资料）。",
+  "enum": [
+    "general",
+    "writing",
+    "revising",
+    "auditing",
+    "setup"
+  ],
+  "type": "string"
+}
    • addedInput schema / properties / systemPromptMode
      Added value: +{
+  "description": "系统提示词档位：off=不注入 / brief=精简（只说明有这套工具） / full=完整（按场景注入对应流程）。",
+  "enum": [
+    "off",
+    "brief",
+    "full"
+  ],
+  "type": "string"
+}
  3. First observed

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose the behavioral effect of each key setting: enabled controls whether the analysis is available, autoAnalyze controls active use during analysis, systemPromptMode and promptScene determine prompt injection and workflow selection, and leanWorkflow reduces tool calls and saves tokens. It does not cover every hidden side effect or permission concern, but the main configurable behavior is transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose and uses parenthesized lists to compress a large amount of parameter semantics into a single sentence. Every clause contributes meaning, with no filler or redundancy, though the single-sentence structure is slightly dense and could benefit from tighter formatting.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 11-parameter get/set tool with no annotations and no output schema, the description explains the core discretionary settings but omits several parameters like tools, features, styleTolerance, creationProfile, and creationProfiles. The schema's rich descriptions compensate for the omissions, but the lack of any statement about what get returns or how set affects current state leaves a meaningful gap in contextual guidance.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, so the schema already fully documents all 11 parameters, including nested objects and enums. The tool description adds only a compressed summary of five main switches and does not provide extra syntax, constraints, or validation details beyond what the schema gives. Thus the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a precise verb+resource statement: '查看或修改句式模式分析的开关状态' (view or modify switch states of sentence-pattern analysis). It clearly identifies the tool as a configuration getter/setter for a specific feature, distinguishing it from sibling tools like novel_sentence_analysis (which performs analysis) and novel_settings (general configuration).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies when to use the tool: whenever the author-agent needs to inspect or change sentence-pattern analysis settings such as enabled, autoAnalyze, systemPromptMode, promptScene, or leanWorkflow. It does not explicitly mention alternatives or exclusions, so it misses the top-tier routing guidance, but the usage context is obvious from the stated purpose.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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