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/relations)<a href="https://agentmods.dev/commands/wordflowlab/novel-writer-skills/relations"><img src="https://agentmods.dev/badge/commands/wordflowlab/novel-writer-skills/relations/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/relations"><img src="https://agentmods.dev/badge/commands/wordflowlab/novel-writer-skills/relations.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 | $0.00009 | $0.00633 |
| Opus 5 | $0.00005 | $0.00316 |
| Sonnet 5 | $0.00002 | $0.00127 |
| Haiku 4.5 | $0.00001 | $0.00063 |
Grade A, and why
relations 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.
What it actually says
角色关系管理
追踪和管理角色之间的关系动态，确保关系发展的合理性。
功能
- 关系网络 - 维护角色之间的关系图谱
- 关系变化 - 记录关系的演变历程
- 派系管理 - 追踪各势力派系的对立与合作
- 情感追踪 - 管理角色间的情感发展
使用方法
执行脚本 {SCRIPT} [操作] [参数]：
update- 更新角色关系show- 显示关系网络history- 查看关系变化历史check- 验证关系逻辑
示例：
{SCRIPT} update 李中庸 allies 沈玉卿 --chapter 61 --note 初入翰林相助
# PowerShell:
{SCRIPT} -Command update -A 李中庸 -Relation allies -B 沈玉卿 -Chapter 61 -Note 初入翰林相助
数据存储
关系数据存储在 spec/tracking/relationships.json：
{
"characters": {
"主角": {
"盟友": ["角色A", "角色B"],
"敌对": ["角色C"],
"爱慕": ["角色D"],
"未知": ["角色E"]
}
},
"factions": {
"改革派": ["主角", "角色A"],
"保守派": ["角色C", "角色F"]
}
}
输出示例
👥 角色关系网络
━━━━━━━━━━━━━━━━━━━━
主角：李中庸
├─ 💕 爱慕：沈玉卿
├─ 🤝 盟友：张居正（隐藏）
├─ 📚 导师：利玛窦
├─ ⚔️ 敌对：申时行派系
└─ 👁️ 监视：东厂
派系对立：
改革派 ←→ 保守派
东林党 ←→ 阉党
最近变化（第60章）：
- 沈玉卿：陌生人 → 相互吸引
- 张居正：未知 → 师承关系
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 · 78 lines · 0 tokens per session scan A 9b3ff222d656
relations is a command published in the GitHub repository wordflowlab/novel-writer-skills (258 stars, last pushed 10mo ago), licensed MIT. It adds 9 tokens to every session and 633 once invoked, about $0.0000 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.
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