Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/wordflowlab/novel-writer-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/wordflowlab/novel-writer-skills/clarify)<a href="https://agentmods.dev/commands/wordflowlab/novel-writer-skills/clarify"><img src="https://agentmods.dev/badge/commands/wordflowlab/novel-writer-skills/clarify/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/wordflowlab/novel-writer-skills/clarify"><img src="https://agentmods.dev/badge/commands/wordflowlab/novel-writer-skills/clarify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00027 | $0.02397 |
| Opus 5.5 | $0.00011 | $0.00959 |
| Sonnet 5.5 | $0.00005 | $0.00479 |
| Haiku 4.5 | $0.00003 | $0.00240 |
Grade A, and why
clarify scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 237 lines — stays where its author put it; the contents beside it link to each section on GitHub.
焦点区域(可选):$ARGUMENTS
目标
检测并减少故事大纲中的歧义或缺失的决策点,通过交互式问答收集澄清信息,并将结果记录在故事文件中。
注意:此澄清流程应在 /plan 之前运行并完成。如果用户明确表示跳过澄清(例如,探索性创作),可以继续,但必须警告下游返工风险会增加。
执行步骤
1. 初始化检查
运行 {SCRIPT} 获取当前故事路径:
- 解析 JSON 获取
STORY_PATH和STORY_NAME - 如果没有找到故事文件,提示用户先运行
/story创建故事大纲 - 加载故事文件内容进行分析
2. 结构化歧义扫描
对故事大纲进行全面扫描,评估每个类别的清晰度(清晰/部分清晰/缺失):
创作定位
- 目标读者群体(年龄段、性别倾向、阅读层次)
- 作品定位(商业爽文/严肃文学/类型小说)
- 预期规模(短篇3-5万/中篇10-20万/长篇50万+)
世界观设定
- 时代背景精确度(具体年份/朝代/架空程度)
- 世界规则(魔法体系/科技水平/社会制度)
- 地理范围(单一城市/多国/大陆/星际)
角色设计
- 主角成长曲线(废柴逆袭/天才型/稳扎稳打)
- 主角性格基调(热血/冷静/腹黑/圣母)
- 配角功能定位(推动剧情/情感支撑/对比反衬)
- 反派智商设定(降智反派/势均力敌/高维碾压)
叙事策略
- 视角选择(第一人称/第三人称限定/上帝视角)
- 时间线结构(线性叙事/倒叙插叙/多线并行)
- 叙事节奏(快节奏爽文/慢热铺垫/张弛有度)
情节核心
- 核心冲突类型(人vs人/人vs自然/人vs社会/人vs自我)
- 主线目标明确度(复仇/成长/拯救/探索)
- 结局倾向(大团圆/悲剧/开放式)
风格基调
- 文风选择(白话流畅/古风典雅/幽默诙谐/冷峻写实)
- 描写侧重(动作场面/心理描写/环境氛围/对话推进)
- 情感基调(热血激昂/压抑黑暗/温馨治愈/虐心催泪)
创作约束
- 敏感内容处理(violence程度/情感尺度)
- 价值观导向(正能量/现实主义/批判性)
- 更新计划(日更/周更/月更)
对每个"部分清晰"或"缺失"的类别生成候选问题,除非:
- 澄清不会实质影响创作方向
- 信息更适合在章节规划阶段确定
3. 生成优先问题队列
内部生成最多5个优先澄清问题,应用以下约束:
- 整个会话最多5个问题
- 每个问题必须可以通过以下方式之一回答:
- 多选题(2-5个互斥选项)
- 简答题(限制5个词以内)
- 只包含对创作方向有实质影响的问题
- 确保类别覆盖平衡,优先高影响领域
- 如果超过5个类别需要澄清,选择(影响力×不确定性)最高的5个
3.5 问题设计原则(对话式理解)
每个问题应当像真人写手在交流,而不是工程师在填表。
核心原则:
- ✅ 先说观察,再问问题:让作者明白"为什么要问这个"
- ✅ 说人话:用创作者的语言,而不是分类学术语
- ✅ 指出影响:让作者理解这个决策会影响什么
- ❌ 避免直接抛问题:不要一上来就"请问你的目标读者是?"
对比示例:
❌ 工程化提问(避免):
问题1:你的目标读者是什么年龄段?
A. 18-25岁 B. 26-35岁 C. 36-45岁
✅ 对话式提问(推荐):
💬 我注意到你的故事有校园元素,但也有职场内容。这两个场景对应的读者群体差异很大——
校园读者喜欢热血成长,职场读者更关注权谋博弈。这会直接影响我们的节奏设计和价值观表达。
所以想先确认:**你主要想写给谁看?**
| 选项 | 说明 |
|------|------|
| A | 学生群体(18-25岁)- 侧重成长和理想主义 |
| B | 职场人士(26-35岁)- 侧重现实和策略思维 |
| C | 通吃(调整为双线叙事,兼顾两者)|
| D | 自定义(请输入你的想法)|
提问结构模板:
💬 [观察到的现象/矛盾点]。[这会影响什么创作决策]。
所以想确认:**[核心问题]**
[选项表格或简答提示]
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 237 lines · 27 tokens per session scan A 3a3c4d7e3882
clarify is a command published in the GitHub repository wordflowlab/novel-writer-skills (271 stars, last pushed 1y ago), licensed MIT. It adds 27 tokens to every session and 2,397 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
clarify compared with commands from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| clarifywordflowlab/novel-writer-skills | Command | 271 | 1y ago | MIT | A | 27 | Claude Code |
| checklistgithub/spec-kit | Command | 148k | yesterday | MIT | A | 13 | Claude Code |
| clarifygithub/spec-kit | Command | 148k | yesterday | MIT | A | 27 | Claude Code |
| specifygithub/spec-kit | Command | 148k | yesterday | MIT | A | 13 | Claude Code |
| analyzegithub/spec-kit | Command | 148k | yesterday | MIT | A | 26 | Claude Code |
| convergegithub/spec-kit | Command | 148k | yesterday | MIT | A | 35 | Claude Code |
| implementgithub/spec-kit | Command | 148k | yesterday | MIT | A | 14 | Claude Code |