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/zhiliyouxian/claude-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/zhiliyouxian/claude-novel-writer/nw-check-entities)<a href="https://agentmods.dev/commands/zhiliyouxian/claude-novel-writer/nw-check-entities"><img src="https://agentmods.dev/badge/commands/zhiliyouxian/claude-novel-writer/nw-check-entities/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/zhiliyouxian/claude-novel-writer/nw-check-entities"><img src="https://agentmods.dev/badge/commands/zhiliyouxian/claude-novel-writer/nw-check-entities.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 | $0.00016 | $0.00466 |
| Opus 5 | $0.00008 | $0.00233 |
| Sonnet 5 | $0.00003 | $0.00093 |
| Haiku 4.5 | $0.00002 | $0.00047 |
Grade A, and why
nw-check-entities 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 12d 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
/nw-check-entities
检查指定项目的实体库，发现重复、冲突和潜在问题。
用法
/nw-check-entities {project_id}
执行流程
调用 consistency-checker Skill 执行以下检查：
1. 重复检测
检查 entities.md 中是否有：
- 标准名称重复
- 同一实体ID出现多次
2. 冲突检测
检查是否有：
- 别名与其他实体的标准名称冲突
- 同一别名属于多个实体
3. 相似度检测
使用编辑距离算法检查：
- 拼写相似的实体（可能是笔误）
- 同音不同字的实体
4. 章节扫描
扫描所有章节，检查：
- 未注册的实体名称
- 实体首次出现章节是否正确
输出示例
🔍 实体检查: dao_immortal
实体总数: 46 个
- 角色: 28
- 地点: 15
- 物品: 9
检查结果:
⚠️ 发现 2 处问题
1. 重复实体
char_005 和 char_018 都叫 "李青云"
建议: 合并或改名
2. 相似名称
"云霄宗" (place_003) 与 "云霄峰" (place_008) 相似
建议: 确认是否为不同地点
✅ 无别名冲突
✅ 无未注册实体
修复建议:
- 全局替换: "将'李青云'改为'李清云'"
- 合并实体: "合并 char_005 和 char_018"
相关命令
/nw-status- 查看项目状态/nw-list- 列出所有项目
相关 Skill
consistency-checker- 执行实际检查操作
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.
- 12d ago First seen · 82 lines · 16 tokens per session scan A 6db1effa1303
nw-check-entities is a command published in the GitHub repository zhiliyouxian/claude-novel-writer (5 stars, last pushed 8mo ago), licensed MIT. It adds 16 tokens to every session and 466 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 2026-08-31.
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.
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.