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-writerWrote 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/write)<a href="https://agentmods.dev/commands/wordflowlab/novel-writer/write"><img src="https://agentmods.dev/badge/commands/wordflowlab/novel-writer/write/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/write"><img src="https://agentmods.dev/badge/commands/wordflowlab/novel-writer/write.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 | $0.00014 | $0.01204 |
| Opus 5.5 | $0.00006 | $0.00482 |
| Sonnet 5.5 | $0.00003 | $0.00241 |
| Haiku 4.5 | $0.00001 | $0.00120 |
Grade A, and why
write 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
执行章节写作任务：
- 运行脚本
{SCRIPT}确定要写作的章节 - 加载相关文件：
- 创作风格：
.specify/memory/writing-constitution.md - 故事大纲：
stories/*/story.md - 章节规划：
stories/*/outline.md - 前文内容：
stories/*/chapters/(如有) - 角色验证规则：
spec/tracking/validation-rules.json(如有) - 角色状态：
spec/tracking/character-state.json - 关系规则：
spec/tracking/relationships.json - 个人语料：
memory/personal-voice.md - 自然化表达：
spec/knowledge/natural-expression.md - 反AI检测：
spec/presets/anti-ai-detection.md
- 创作风格：
写作前验证提醒
如果存在验证规则文件，执行以下检查：
- 显示主角正确名称和别名
- 列出本章将出现的角色及其正确称呼
- 提醒常见错误（从validation-rules.json的common_errors读取）
示例输出：
📝 写作提醒
━━━━━━━━━━━━━━━━━━━
主角：李中庸（中庸、李公子）
配角：沈玉卿 → 主角称呼为"公子"
⚠️ 避免使用：李明、张华、主角
-
应用反AI检测策略：
- 词汇优化：替换AI特征词为口语表达
- 句法自然化：长短句交错，加入口语特征
- 认知模拟：体现人类思维的不完美性
- 缺陷植入：适度的错别字和标点随意（每2000字1处）
- 个性标记：应用personal-voice.md的个人特征
-
根据章节大纲创作内容：
- 开场：吸引读者，承接前文
- 发展：推进情节，深化人物
- 转折：制造冲突或悬念
- 收尾：适当收束，引出下文
-
确保内容符合：
- 设定的创作风格
- 角色性格一致性
- 世界观规则
- 情节逻辑
- 自然化要求：避免过于完美的表达
-
写作后快速验证（如果存在validation-rules.json）：
- 扫描生成内容中的角色名称
- 检查是否有forbidden列表中的错误名称
- 验证称呼是否符合relationships规则
- 如发现问题，立即提示并建议修正
-
AI检测自检：
- 检查是否有连续3句结构相似
- 检查用词是否过于书面化
- 确认有适度的口语化特征
- 验证文本不过于完美
-
将章节内容写入对应文件
-
更新写作进度和任务状态
写作要点：
- 保持风格一致性
- 注意伏笔的埋设和回收
- 对话要符合角色身份
- 描写要有画面感
- 每章要有明确的推进作用
- 反AI要点：
- 自然化表达优于完美文字
- 适度缺陷增加真实感
- 个人特征贯穿全文
追踪数据自动更新
写作完成后，自动执行以下更新：
-
更新情节追踪
- 更新
spec/tracking/plot-tracker.json的当前章节 - 标记完成的情节节点
- 记录新增的伏笔
- 更新
-
更新时间线
- 提取章节中的时间信息
- 更新
spec/tracking/timeline.json - 检查时间连续性
-
更新角色关系
- 识别关系变化
- 更新
spec/tracking/relationships.json - 记录关系演变历程
-
更新角色状态
- 记录角色位置变化
- 更新
spec/tracking/character-state.json - 追踪角色发展
-
生成追踪提醒
✅ 第N章写作完成，追踪数据已更新 建议执行： - /plot-check 验证情节连贯性 - /timeline 检查时间逻辑 - /relations 确认关系变化 - /track --check 批量验证最近章节（推荐每10章执行一次）
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 · 127 lines · 14 tokens per session scan A fe057eebe01b
write is a command published in the GitHub repository wordflowlab/novel-writer (957 stars, last pushed 1y ago), licensed MIT. It adds 14 tokens to every session and 1,204 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.
write compared with commands from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| writewordflowlab/novel-writer | Command | 957 | 1y ago | MIT | A | 14 | 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 |