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 deepseek-html-processorgit 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/deepseek-html-processor)<a href="https://agentmods.dev/skills/shan8065/novel-writing-agent-platform/deepseek-html-processor"><img src="https://agentmods.dev/badge/skills/shan8065/novel-writing-agent-platform/deepseek-html-processor/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/deepseek-html-processor"><img src="https://agentmods.dev/badge/skills/shan8065/novel-writing-agent-platform/deepseek-html-processor.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 | $0.00049 | $0.00962 |
| Opus 5 | $0.00024 | $0.00481 |
| Sonnet 5 | $0.00010 | $0.00192 |
| Haiku 4.5 | $0.00005 | $0.00096 |
Grade A, and why
deepseek-html-processor 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 8d 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
DeepSeek TXT处理器
功能
专业的DeepSeek聊天记录TXT文件处理工具，专门处理从DeepSeek复制保存的对话内容：
- 提取用户与AI的完整对话历史
- 识别和分离角色设定、章节内容、故事大纲等不同类型的信息
- 支持批量处理多个TXT文件
- 输出结构化的纯文本内容供其他智能体使用
使用场景
- 有多个从DeepSeek复制保存的TXT聊天记录需要整理时
- 需要从TXT中提取角色设定、故事大纲、章节内容时
- 需要把TXT格式的对话历史转换为可读的文本格式时
- 需要为其他小说创作智能体提供参考资料时
- 需要节省token消耗，只保留有效内容时
处理内容类型
对话历史提取
- 完整的用户提问历史
- AI的回答和创作内容
- 对话的时间顺序和上下文关系
- 多轮迭代的内容版本
角色设定识别
- 角色基本信息（姓名、年龄、职业等）
- 外貌特征和性格描述
- 背景故事和成长经历
- 能力和特殊技能
- 人际关系网
故事内容提取
- 章节正文内容
- 故事大纲和分集规划
- 情节梗概和关键节点
- 对话和场景描写
- 设定说明和世界观
其他创作资料
- 写作思路和创作笔记
- 参考资料和灵感来源
- 修改记录和版本对比
- 反馈意见和改进建议
输出格式
对话历史格式
## 对话历史
### 用户输入 1
[用户的原始问题或指令]
### AI回复 1
[AI的完整回答内容]
---
### 用户输入 2
[下一个问题]
角色档案格式
## 角色档案
### [角色名]
- 姓名：
- 年龄：
- 职业：
- 外貌：
- 性格：
- 背景：
- 能力：
章节内容格式
## 第X章：[章节标题]
[完整的章节正文内容]
与其他智能体协作
配合lore-organizer（资料整理智能体）
- 使用本工具提取TXT中的角色设定
- 将结果传递给lore-organizer
- 由lore-organizer整理成规范的角色档案
配合story-writer（小说写作智能体）
- 使用本工具提取TXT中的章节内容和大纲
- 将结构化内容提供给story-writer
- 由story-writer基于已有内容继续创作
配合coherence-checker（连贯性检查智能体）
- 使用本工具提取完整对话历史
- 提供给coherence-checker作为参考
- 确保新创作内容与历史设定一致
批量处理功能
目录扫描
- 自动扫描指定目录下所有DeepSeek TXT文件
- 识别文件名中的章节号、主题等信息
- 按顺序组织和整理多个文件
合并功能
- 将多个相关TXT文件的内容合并
- 保持时间顺序和逻辑连贯性
- 去除重复内容和冗余信息
使用示例
示例1：单个文件处理
输入：处理"崩坏3故事1.txt" 输出：提取的对话历史、角色设定、章节内容
示例2：批量处理
输入：处理"与deepseek一起创作小说章节"目录下所有TXT文件 输出：按章节组织的完整故事内容
示例3：为其他智能体准备素材
输入：从TXT中提取所有角色信息 输出：结构化的角色档案供lore-organizer使用
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.
- 8d ago First seen · 133 lines · 49 tokens per session scan A f58d892bbebd
deepseek-html-processor is a skill published in the GitHub repository shan8065/novel-writing-agent-platform (2 stars, last pushed 4mo ago), licensed MIT. It adds 49 tokens to every session and 962 once invoked, about $0.0002 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.
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