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 skills add shan8065/novel-writing-agent-platform --skill honkai-character-integratorgit clone --depth 1 https://github.com/shan8065/novel-writing-agent-platformWrote 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/skills/shan8065/novel-writing-agent-platform/honkai-character-integrator)<a href="https://agentmods.dev/skills/shan8065/novel-writing-agent-platform/honkai-character-integrator"><img src="https://agentmods.dev/badge/skills/shan8065/novel-writing-agent-platform/honkai-character-integrator/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/skills/shan8065/novel-writing-agent-platform/honkai-character-integrator"><img src="https://agentmods.dev/badge/skills/shan8065/novel-writing-agent-platform/honkai-character-integrator.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 | $0.00050 | $0.01519 |
| Opus 5 | $0.00025 | $0.00759 |
| Sonnet 5 | $0.00010 | $0.00304 |
| Haiku 4.5 | $0.00005 | $0.00152 |
Grade A, and why
honkai-character-integrator 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.
How it starts
The opening of the file, as written. The whole thing — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
崩坏3角色整合器
功能
专业的崩坏3角色整合专家,负责:
- 读取和解析崩坏3角色文件夹中的PDF文件
- 提取角色的完整信息(背景、能力、性格、外貌等)
- 将崩坏3角色自然融入现有的故事世界观
- 建立崩坏3角色与原创角色的关系网
- 设计角色在故事中的定位和作用
- 确保角色融合的合理性和连贯性
使用场景
- 需要将崩坏3角色融入故事时
- 需要了解崩坏3角色详细信息时
- 需要设计角色互动关系时
- 需要为故事添加新角色时
- 需要确保角色融合合理性时
核心功能
崩坏3角色信息提取
- 读取崩坏3角色文件夹中的所有PDF文件
- 提取角色基本信息(姓名、称号、身份等)
- 解析角色背景故事和经历
- 提取角色能力和战斗技能
- 分析角色性格特点和外貌特征
- 理解角色在崩坏3原作中的定位
世界观融合设计
- 分析现有故事世界观(SCP基金会+原创设定)
- 设计崩坏3角色进入故事的合理方式
- 建立律者能力与SCP能力的对应关系
- 调整角色设定以适应新世界观
- 确保能力体系的平衡性
角色关系网构建
- 设计崩坏3角色与原创角色的相遇方式
- 建立角色之间的互动关系
- 设计友情、敌对、合作等关系模式
- 创建角色发展弧线
- 规划角色在故事中的重要节点
故事定位规划
- 确定每个崩坏3角色在故事中的作用
- 设计角色的登场场景
- 规划角色的成长和变化
- 预留角色的重要剧情位置
- 设计角色的高光时刻
崩坏3角色列表
已有的崩坏3角色
- 终焉之律者 - 终结一切的律者
- 真理之律者 - 掌握真理的律者
- 始源之律者 - 起源的律者
- 死生之律者 - 掌控生死的律者
- 真我·人之律者 - 代表人性的律者
- 嗨♪爱愿妖精♥ - 特殊角色
处理流程
-
读取崩坏3角色资料
- 扫描崩坏3角色文件夹
- 读取所有PDF文件
- 提取角色完整信息
-
分析现有世界观
- 了解原创角色设定
- 理解SCP能力体系
- 把握故事基调
-
设计融合方案
- 设计角色进入方式
- 调整能力设定
- 建立关系网络
-
整合到故事中
- 确定角色定位
- 设计登场情节
- 规划发展弧线
-
输出完整方案
- 生成角色融合档案
- 提供关系网络图
- 给出故事建议
输出格式
崩坏3角色融合档案
## 崩坏3角色融合:[角色名]
### 原作信息
- **原作称号**:
- **原作身份**:
- **原作背景**:
- **原作能力**:
### 融合后设定
- **新身份**:
- **进入故事的方式**:
- **调整后的背景**:
### 能力融合
- **原作能力**:
- **与SCP世界观的融合**:
- **能力表现调整**:
- **能力限制与平衡**:
### 角色关系
- **与山天远的关系**:
- **与其他原创角色的关系**:
- **与其他崩坏3角色的关系**:
### 故事定位
- **在故事中的作用**:
- **预计登场章节**:
- **重要剧情节点**:
- **角色发展弧线**:
### 融合合理性说明
- [说明为什么这样融合是合理的]
- [如何确保与现有设定不冲突]
角色关系网络图
## 角色关系网络
### 核心关系
- 山天远 ↔ [崩坏3角色1]:[关系描述]
- 山天远 ↔ [崩坏3角色2]:[关系描述]
- ...
### 崩坏3角色之间
- [角色1] ↔ [角色2]:[关系描述]
- ...
### 阵营划分
- **主要阵营**:
- 成员:
- **其他阵营**:
- 成员:
与其他智能体协作
配合 lore-organizer(资料整理智能体)
- 本工具整合崩坏3角色
- 将融合档案传递给lore-organizer
- 由lore-organizer纳入整体世界观
配合 story-writer(小说写作智能体)
- 提供崩坏3角色融合档案
- 建议登场场景和互动情节
- 确保角色表现符合设定
配合 coherence-checker(连贯性检查智能体)
- 提供融合设定基准
- 协助检查角色融合是否合理
- 发现设定矛盾
配合 character-scp-integrator(角色SCP整合器)
- 共享角色信息
- 协调能力体系
- 确保整体平衡
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 · 190 lines · 50 tokens per session scan A 28a06146a06e
honkai-character-integrator is a skill published in the GitHub repository shan8065/novel-writing-agent-platform (3 stars, last pushed 5mo ago), licensed MIT. It adds 50 tokens to every session and 1,519 once invoked, about $0.0003 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 skills, from other repositories
pydicom
Use pydicom to read, inspect, write, transform, and safely preflight local DICOM datasets and pixel data. Applies to DICOM metadata, transfer syntaxes, compression plugins, frames, private elements, JSON, and bounded de-identification review.
foundry-hosted-agent-validation
Step-by-step process for validating a Python Foundry hosted agent sample (under python/samples/04-hosting/foundry-hosted-agents/) end to end — running it locally (native runtime and azd ai agent run) and after deploying it to an Azure AI Foundry project with azd. Use this when asked to validate a hosted agent sample.
skill-doc-delivery
Convert markdown to DOCX, PPTX, XLSX, PDF office documents — use when you need exportable deliverables.
pdf-extract-create-workflow
Complete PDF lifecycle: download, extract, and generate structured documents with reportlab.
document-direct-python
Use direct Python execution for reliable document creation including spreadsheets, PDFs, and structured reports.
parse-document
Convert a PDF, scan, image of a page, or office file to clean markdown through the connected Superlinked MCP edge, so the source document is not read into model context directly. Use when the user asks to read, parse, OCR, extract from, summarize, or answer questions about a document.