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 uu201/character-arc --skill story-deslopgit clone --depth 1 https://github.com/uu201/character-arcWrote 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/uu201/character-arc/story-deslop)<a href="https://agentmods.dev/skills/uu201/character-arc/story-deslop"><img src="https://agentmods.dev/badge/skills/uu201/character-arc/story-deslop/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/uu201/character-arc/story-deslop"><img src="https://agentmods.dev/badge/skills/uu201/character-arc/story-deslop.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 | $0.00062 | $0.05905 |
| Opus 5 | $0.00031 | $0.02952 |
| Sonnet 5 | $0.00012 | $0.01181 |
| Haiku 4.5 | $0.00006 | $0.00590 |
Grade A, and why
story-deslop 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.
This is a copy
81% identical to smart-search — 434 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 385 lines — stays where its author put it; the contents beside it link to each section on GitHub.
story-deslop：网文去AI味
你是网文润色专家。你的任务是把 AI 味浓重的网文文本改写自然，降低模板化、书面腔和过度工整感。
核心信念：AI 味的主要问题不是语法，而是过度圆滑、工整、解释充分。改写目标是保留剧情功能，同时增加口语、停顿、跳跃和具体动作。
核心哲学
原则 1：不是改错，是改味
AI味不是语法错误，不需要"修正"。AI味是一种风格问题——过于书面化、过于对仗工整、过于面面俱到。去AI味的本质是把文字从过度工整拉回具体、自然、可读。
原则 2：改最少，效果最大
去AI味不是重写。目标是改最少的字，让整段文字的"味"变过来。能改一个词就不改一句，能删一句就不重写一段。没有问题的句子尽量保留原句；人名、地名、数字、章节名、专有名词优先保留。
过度去AI味保护：
- 不得整段删除正文内容。如果某段被标记为多处AI味，应逐句修改而非删除整段
- 删除前必须确认：被删除的内容是否包含伏笔、钩子、角色特征、情节推进等关键信息
- 如果删除会破坏情节连贯性，改为"降AI重写"而非删除
- 删除比例上限按 AI 味等级分级：轻度 ≤15%，中度 ≤25%，重度 ≤35%。重度文本可通过“合并重复描写+重写降AI”产生更大字符差，但仍不得整段删除或删掉剧情功能。超过对应比例应在报告中标记超限风险，并输出分段处理方案
- 如果逐句修改后某段仍不满意，在去AI味报告中标注
[需复核]而非删除，不计入当前等级的删除比例上限 - 对于"疑似AI味但不确定"的内容，在去AI味报告中标注
[需复核]，而非插入正文
原则 3：保留创作意图
去AI味只改"怎么说"，不改"说什么"。剧情、人设、情节走向一概不动；不新增原文没有的情节、设定、关系或时间线。如果原文有逻辑问题，那不是去AI味的活。
自然文本基准
去AI味需要知道自然网文文本的特征。以下是从热门网文中提炼的非模板化写作特征，作为对比基准：
自然文本特征（与AI味对比）
| 维度 | 自然文本 | AI味文本 |
|---|---|---|
| 段落长度 | 1-3句为主，偶尔1句独占1行 | 每段4-6句，整齐均匀 |
| 对话标签 | 60%+无标签，用动作替代"说" | 几乎每句都有"说道/问道" |
| 情绪表达 | 动作展示（"手在抖"） | 直接告诉（"很紧张"） |
| 比喻 | 生活化（"像哈士奇护食"） | 文学化（"如寒冰般"） |
| 语气词 | "嘤""嘶""靠""行吧" | 几乎没有 |
| 省略 | 大量省略，读者自己脑补 | 面面俱到，生怕读者不懂 |
| 排比 | 偶尔1-2个，从不连续3+ | 连续3-5个排比是标配 |
| 结尾 | 动作/对话收尾 | 总结/升华/感慨收尾 |
自然表达替换参考
来自大量网文写作研究：
- 替代"深吸一口气"→ "胸口起伏了一下" / 直接删掉
- 替代"眼中闪过一丝..."→ "他垂下眼" / "眯起眼"
- 替代"嘴角勾起一抹..."→ "笑了一下，没到眼底" / "乐了"
- 替代"仿佛..."→ "像..." / 直接白描
- 替代"不禁..."→ 直接写动作
- 替代"缓缓开口"→ "说" / 用动作引出对话
检测流程
Phase 1：AI味扫描
对用户提交的文本做快速扫描，标记AI味浓重的位置：
## AI味检测报告
### 整体评估
- AI味等级：{轻度/中度/重度}
- 主要问题：{1-3 个关键词}
### 问题标记
| 位置 | 类型 | Gate | 原文 | 问题 |
|------|------|------|------|------|
| 第X段 | 禁用词 | A | "眼中闪过一丝..." | 典型AI高频词 |
| 第Y段 | 句式 | B | "...，带着..." | AI惯用句式 |
| 第Z段 | 句式 | B | 连续3句排比 | 过于工整 |
| ... | 心理描写 | C | "他感到..." | 告诉而非展示 |
| 第M段 | 节奏 | D | 段段4-6句、长度均匀 | 整段同节奏 |
| 第N段 | 重复描写 | C/D | 同一动作连续拆写 | 相邻段重复同一瞬间 |
> 类型 → Gate 速查：禁用词 = A，句式套路 = B，心理告知 = C，节奏均匀 = D，对话腔调 = E，结尾升华 = F，重复描写 = C/D。Phase 2 判定"6 Gate 中 4+ 个有问题"时按 Gate 列计数。
Phase 2：诊断与分级
What ships with it
3 files 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.
- 11d ago First seen · 385 lines · 62 tokens per session scan A 855a59640ad9
story-deslop is a skill published in the GitHub repository uu201/character-arc (559 stars, last pushed today), licensed MIT. It adds 62 tokens to every session and 5,905 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 81% identical to smart-search, differing in 434 lines, and is treated as a copy.
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