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.
npx agentmods add commands/wordflowlab/novel-writer/tasksgit 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/tasks)<a href="https://agentmods.dev/commands/wordflowlab/novel-writer/tasks"><img src="https://agentmods.dev/badge/commands/wordflowlab/novel-writer/tasks.svg" alt="Measured on agentmods" 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 | $0.00013 | $0.00608 |
| Opus 5 | $0.00006 | $0.00304 |
| Sonnet 5 | $0.00003 | $0.00122 |
| Haiku 4.5 | $0.00001 | $0.00061 |
Grade A, and why
tasks 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 6d 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.
What it actually says
基于创作计划生成具体的、可执行的任务列表。
目标
将宏观计划转化为微观任务，让创作变得可管理、可追踪。
执行步骤
1. 加载计划文档
运行 {SCRIPT} 加载：
- 创作计划：
stories/*/creative-plan.md - 章节架构信息
- 时间线和依赖关系
2. 生成任务列表
创建 stories/*/tasks.md，包含：
核心写作任务
## 写作任务
### 高优先级 [必须首先完成]
- [ ] [P0] 第1章：开篇钩子 (3000字)
- [ ] [P0] 角色档案：主角详细设定
- [ ] [P0] 世界观：基础规则设定
### 中优先级 [正常推进]
- [ ] [P1] 第2-5章：故事展开 (每章3000字)
- [ ] [P1] 角色档案：主要配角
- [ ] [P1] 场景设定：重要地点
### 低优先级 [可选完善]
- [ ] [P2] 番外：角色前传
- [ ] [P2] 设定集：详细世界观
任务标记说明
[P]- 可并行执行[依赖:X]- 需要先完成任务X[P0/P1/P2]- 优先级标记
3. 任务排序和分组
- 按优先级分组
- 识别依赖关系
- 标记可并行任务
- 估算完成时间
4. 生成执行计划
## 执行计划
### 第一阶段（第1周）
并行任务组1：
- 主角设定 [P]
- 世界观基础 [P]
- 第1章草稿 [P]
### 第二阶段（第2-3周）
串行任务：
- 第2章 [依赖:第1章]
- 第3章 [依赖:第2章]
并行任务组2：
- 配角设定 [P]
- 场景设计 [P]
5. 输出任务统计
- 总任务数
- 预计总字数
- 预计完成时间
- 关键里程碑
提示下一步：开始执行 /write 或查看特定任务详情。
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.
- 6d ago First seen · 86 lines · 13 tokens per session scan A 25a612fc5356
tasks is a command published in the GitHub repository wordflowlab/novel-writer (940 stars, last pushed 10mo ago), licensed MIT. It adds 13 tokens to every session and 608 once invoked, about $0.0001 per session on Opus 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.