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 malue-ai/dazee-small --skill writing-analyzergit clone --depth 1 https://github.com/malue-ai/dazee-smallWrote 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/malue-ai/dazee-small/writing-analyzer)<a href="https://agentmods.dev/skills/malue-ai/dazee-small/writing-analyzer"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/writing-analyzer/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/malue-ai/dazee-small/writing-analyzer"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/writing-analyzer.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 | $0.00024 | $0.00584 |
| Opus 5 | $0.00012 | $0.00292 |
| Sonnet 5 | $0.00005 | $0.00117 |
| Haiku 4.5 | $0.00002 | $0.00058 |
Grade A, and why
writing-analyzer 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 9d 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
写作风格分析
分析文本的写作风格、可读性、语气和结构，给出改进建议。
使用场景
- 用户说「分析一下我的写作风格」「这篇文章写得怎么样」
- 用户想了解自己的文字特点
- 帮助用户在不同场景切换风格（正式/口语/学术/营销）
执行方式
直接使用 LLM 能力进行深度分析，无需外部工具。
分析维度
对用户提供的文本，从以下维度分析：
- 语气风格：正式/半正式/口语/学术/营销/文学
- 句式特点：长句多还是短句多、主动被动、排比反问
- 用词偏好：书面词汇/口语词汇、专业术语密度、修饰词频率
- 结构习惯：段落长度、转折方式、开头结尾模式
- 可读性：信息密度、逻辑清晰度、阅读难度
- 情感倾向：积极/中性/消极、热情/克制
输出格式
## 写作风格分析
**整体风格**：[一句话概括]
### 语气
- 类型：[正式/口语/...]
- 特点：[具体描述]
### 句式
- 平均句长：[短/中/长]
- 特点：[具体描述]
### 用词
- 词汇层次：[通俗/专业/文学]
- 突出特征：[具体描述]
### 改进建议
1. [具体建议]
2. [具体建议]
3. [具体建议]
多文本对比
当用户提供多篇文本时，可以对比风格差异：
## 风格对比
| 维度 | 文本 A | 文本 B |
|------|--------|--------|
| 语气 | 正式 | 口语 |
| 句长 | 长 | 短 |
| 用词 | 专业 | 通俗 |
安全规则
- 分析结果客观中性，不评判内容价值观
- 仅分析写作技巧，不评价观点对错
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.
- 9d ago First seen · 80 lines · 24 tokens per session scan A 98948a0265aa
writing-analyzer is a skill published in the GitHub repository malue-ai/dazee-small (36 stars, last pushed 5mo ago), licensed MIT. It adds 24 tokens to every session and 584 once invoked, about $0.0001 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 2026-09-03.
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