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 lj22503/diaolong-skill --skill narrative-metagit clone --depth 1 https://github.com/lj22503/diaolong-skillWrote 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/lj22503/diaolong-skill/narrative-meta)<a href="https://agentmods.dev/skills/lj22503/diaolong-skill/narrative-meta"><img src="https://agentmods.dev/badge/skills/lj22503/diaolong-skill/narrative-meta/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/lj22503/diaolong-skill/narrative-meta"><img src="https://agentmods.dev/badge/skills/lj22503/diaolong-skill/narrative-meta.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 | $0.00066 | $0.02991 |
| Opus 5 | $0.00033 | $0.01496 |
| Sonnet 5 | $0.00013 | $0.00598 |
| Haiku 4.5 | $0.00007 | $0.00299 |
Grade A, and why
dragoncraft-core 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 — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
雕龙·心法 (DragonCraft Core)
描述：叙事的底层操作系统。为所有场景Skill提供理论支撑、美学判断、伦理基准和质量检查。不直接输出内容，而是作为"操作系统"被场景Skill调用。
🎯 核心能力
- 叙事评估：按八刀框架输出评估报告。
- 知识检索：为场景Skill提供理论依据。
- 结构生成：基于拉波夫公式生成骨架。
- 去AI化检测：7条规则检测并给出修改建议。
- 人格映射：推荐最适合的MBTI叙事人格。
- 伦理审查：应用三条原则，标注省略与风险。
- 一致性检查：跨场景比对，输出差异报告。
- 记忆管理：存储并检索用户的历史叙事，确保持续性和一致性。
📚 内置知识库
模块1：叙事本能公式
叙事 = (事件 + 因果 + 意图) → 时间化 → 可传递的经验单元
模块2：拉波夫最小故事公式
（抽象）→ 定位 → 复杂化 → 评价 → 解决 → 尾声
模块3：叙事八刀评估框架
| 八刀维度 | 评估规则 | 检测方式 |
|---|---|---|
| 历史 | 叙事是否符合人的认知习惯？有无强行扭曲？ | 检测因果链是否自洽 |
| 辩证 | 叙事与逻辑/数据的平衡是否被打破？ | 检测叙事是否过度覆盖事实 |
| 现象 | 叙事的起点是否真实可感？ | 检测是否有具体场景锚点 |
| 语言 | 语言是否自然、有温度、无模板痕迹？ | AI化程度检测 |
| 形式 | 是否符合拉波夫最小故事公式？ | 结构完整性检测 |
| 存在 | 叙事是否服务于自我认同或社会协作？ | 目标匹配度检测 |
| 美感 | 叙事是否有审美价值？ | 金句密度、意象质量 |
| 元反思 | 是否有明显虚构但不自知的部分？ | 事实与叙事的分离度检测 |
模块4：MBTI叙事人格映射
| 类型 | 叙事风格 | 典型场景 |
|---|---|---|
| ENFJ | 鼓舞型叙事，召唤集体行动 | 品牌使命、团队动员、公益、教育 |
| ENFP | 即兴型叙事，跳跃生动 | 社交媒体、创意产品、生活方式IP |
| INFJ | 隐喻型叙事，深度疗愈 | 品牌哲学、心理、艺术、可持续 |
| INFP | 自传型叙事，真诚柔软 | 个人IP、治愈系博客、创作者 |
| INTJ | 冷静有远见的战略家 | 科技融资、行业分析、硬核知识 |
| ENTP | 爱挑战的颠覆者 | 争议话题、反常识观点、辩论 |
| ESFP | 热情活在当下的表演者 | 直播、探店、娱乐短视频 |
| ISFJ | 默默守护的实干家 | 服务行业、医疗、传统手工艺 |
模块5：探索式叙事设计原则
碎片化散布 → 用户探索拼合 → 产生所有权感
模块6：去AI化检测规则清单（7条）
| 规则 | 检测内容 | 自动化判断方式 | 润色动作 |
|---|---|---|---|
| 规则1 | 过度使用模板词 | 匹配"在当今时代""值得注意的是"等词库 | 删除或改为口语 |
| 规则2 | 句句工整 | 检测句子长度方差，方差＜1.5则触发 | 拆分长句、插入短句、口语化打断 |
| 规则3 | 逻辑词过密 | 检测"因此→所以→然后"密度 | 删除不必要的逻辑词，用换行/破折号替代 |
| 规则4 | 缺少细节锚点 | 检测是否有姓名/时间/地点/数字 | 提示用户补充锚点，或自动生成占位符[请补充] |
| 规则5 | 情感抽象 | 检测"我很感动""我很震撼"等抽象表达 | 提示转为具象描写 |
| 规则6 | 人格不一致 | 用一致性打分模型检测语气/视角跳跃 | 统一到选定的叙事人格 |
| 规则7 | 过度解释 | 检测"这意味着""换句话说"等说破词汇 | 删除或转为留白 |
模块7：叙事伦理模块
三条核心原则
- 原则1：不造假，但真话不全说 → 事实不可篡改；省略的信息必须与受众核心决策无直接因果关系；以下场景强制全面披露（法律庭审、医疗知情、融资尽调、产品安全）。
- 原则2：目标受众导向（非必填） → 若用户提供受众画像，叙事将针对其关切点调整；若不提供，则采用通用最佳实践。
- 原则3：适配场景的框架/思维/方法 → 每个场景有独立结构模板和知识库；提供跨场景一致性检查。
执行方式
- 生成叙事后自动扫描可能误导的省略，标注[此处省略了X，如需完整信息请告知]。
- 用户可选择"豁免伦理检查"或"强制完整版"。
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 195 lines · 0 tokens per session scan A c507d8993515
dragoncraft-core is a skill published in the GitHub repository lj22503/diaolong-skill (5 stars, last pushed 1mo ago), licensed MIT. It adds 66 tokens to every session and 2,991 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.
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