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/world-check)<a href="https://agentmods.dev/commands/wordflowlab/novel-writer/world-check"><img src="https://agentmods.dev/badge/commands/wordflowlab/novel-writer/world-check/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/world-check"><img src="https://agentmods.dev/badge/commands/wordflowlab/novel-writer/world-check.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 | $0.00011 | $0.00407 |
| Opus 5 | $0.00005 | $0.00204 |
| Sonnet 5 | $0.00002 | $0.00081 |
| Haiku 4.5 | $0.00001 | $0.00041 |
Grade A, and why
world-check 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 10d 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
世界观一致性检查
确保故事中的世界观设定保持前后一致，避免矛盾和冲突。
检查范围
- 设定一致性 - 验证规则、法则、体系的一致
- 地理逻辑 - 检查地点、距离、方位的合理性
- 文化连贯 - 确保风俗、语言、传统的统一
- 科技/魔法水平 - 验证能力范围和限制
使用方法
执行脚本 {SCRIPT}，将会：
- 扫描
spec/knowledge/world-setting.md - 分析已写章节中的设定描述
- 对比查找矛盾和冲突
- 生成一致性报告
知识库结构
世界观设定存储在 spec/knowledge/ 目录：
world-setting.md- 核心世界观locations.md- 地点描述culture.md- 文化风俗rules.md- 特殊规则
输出示例
🌍 世界观一致性报告
━━━━━━━━━━━━━━━━━━━━
✅ 检查通过：23项
⚠️ 潜在问题：2项
⚠️ 发现的问题：
1. 第15章提到"三日路程"，但按地图应为五日
2. 第23章的官职名称与第3章不一致
📚 设定统计：
- 地点：15个
- 组织：8个
- 特殊规则：5条
- 专有名词：47个
💡 建议创建术语表以保持一致性
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.
- 10d ago First seen · 54 lines · 11 tokens per session scan A dde3dc024c8d
world-check is a command published in the GitHub repository wordflowlab/novel-writer (943 stars, last pushed 10mo ago), licensed MIT. It adds 11 tokens to every session and 407 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.