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/analyze)<a href="https://agentmods.dev/commands/wordflowlab/novel-writer-skills/analyze"><img src="https://agentmods.dev/badge/commands/wordflowlab/novel-writer-skills/analyze/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/analyze"><img src="https://agentmods.dev/badge/commands/wordflowlab/novel-writer-skills/analyze.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 | $0.00025 | $0.09359 |
| Opus 5 | $0.00013 | $0.04679 |
| Sonnet 5 | $0.00005 | $0.01872 |
| Haiku 4.5 | $0.00003 | $0.00936 |
Grade A, and why
analyze 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 11d 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 — 1,001 lines — stays where its author put it; the contents beside it link to each section on GitHub.
对小说项目进行智能化综合分析。根据当前创作阶段,自动选择执行框架一致性分析(write 之前)或内容质量分析(write 之后)。
核心理念
一个命令,双重智能:
- 📐 框架分析:在写作前验证规格、计划、任务的一致性(类似 spec-kit)
- 📝 内容分析:在写作后验证已完成内容的质量和符合度
克制而不简陋:
- 用户只需执行
/analyze,系统自动判断应该执行哪种分析 - 支持手动指定模式:
$ARGUMENTS --type=framework或--type=content
执行流程
1. 智能阶段检测
运行 {SCRIPT} 获取当前创作状态:
{
"analyze_type": "framework|content",
"chapter_count": 0,
"has_spec": true,
"has_plan": true,
"has_tasks": true,
"story_dir": "/path/to/story",
"reason": "原因说明"
}
2. 决策逻辑
解析用户参数 $ARGUMENTS:
手动指定模式(优先级最高):
- 包含
--type=framework→ 强制框架分析 - 包含
--type=content→ 强制内容分析
🆕 专项分析模式(新增):
- 包含
--focus=opening→ 开篇专项分析(重点分析前3章) - 包含
--focus=pacing→ 节奏专项分析(重点分析爽点/冲突分布) - 包含
--focus=character→ 人物专项分析(重点分析人物弧光) - 包含
--focus=foreshadow→ 伏笔专项分析(重点分析伏笔埋设与回收) - 包含
--focus=logic→ 逻辑专项分析(重点查找逻辑漏洞) - 包含
--focus=style→ 风格专项分析(重点检查文笔一致性)
自动判断模式:
- 章节数 = 0 → 框架分析
- 章节数 < 3 → 框架分析(但提示可以继续写作)
- 章节数 ≥ 3 → 内容分析
3. 执行对应分析
根据决策结果,执行以下两种分析之一。
模式A:框架一致性分析
目标:在写作前验证准备工作是否充分,确保规格、计划、任务之间无矛盾。
A1. 加载基准文档
- 宪法文件:
.specify/memory/constitution.md - 规格文件:
stories/*/specification.md - 计划文件:
stories/*/creative-plan.md - 任务文件:
stories/*/tasks.md
A2. 覆盖率分析
检查所有规格需求是否都有对应的计划和任务:
## 覆盖率分析报告
### P0 需求覆盖
- [需求1:主角成长线] → ✅ 计划第3章段、任务#5-8
- [需求2:反派设定] → ⚠️ 计划中提及,但无具体任务
- [需求3:悬念设置] → ❌ 计划和任务中均未覆盖
### P1 需求覆盖
覆盖率:75% (3/4)
### P2 需求覆盖
覆盖率:50% (2/4)
### 任务完整性
- 所有计划章节是否有对应任务:⚠️ 第10-12章缺少任务
- 任务是否涵盖所有关键场景:✅ 是
A3. 一致性检查
验证文档之间是否存在矛盾:
## 一致性检查报告
### 规格 ↔ 计划
- ✅ 主题表达一致
- ⚠️ 规格要求"快节奏",但计划前5章节奏较慢
- ❌ 规格禁止"感情戏过多",但计划第6-8章大量感情线
### 计划 ↔ 任务
- ✅ 所有计划章节都有任务
- ⚠️ 任务总字数预估 150K,但计划目标是 100K
- ❌ 计划要求第5章是高潮,但任务标注为"过渡章节"
### 宪法合规
- ✅ 计划符合创作宪法的价值观
- ✅ 任务分解符合质量标准
A4. 逻辑问题预警
分析故事线设计中的潜在逻辑漏洞:
## 逻辑问题预警
### 时间线冲突
- ⚠️ 第3章是"三年后",但第5章角色提到"两年前的事",时间对不上
### 角色能力矛盾
- ❌ 第2章主角"不会武功",第4章任务描述"使用剑术击败敌人"
### 伏笔未规划
- ⚠️ 第1章埋伏笔"神秘令牌",但后续章节无回收计划
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.
- 11d ago First seen · 1,001 lines · 25 tokens per session scan A d06d383f44fb
analyze is a command published in the GitHub repository wordflowlab/novel-writer-skills (258 stars, last pushed 10mo ago), licensed MIT. It adds 25 tokens to every session and 9,359 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.