huashu-skills is a catalogue of Agent Skills, which are reusable instruction packages that extend coding agents such as Claude Code, Codex, and Kimi Code for particular tasks. It organizes skills for design, research, document conversion, content creation, and other workflows, and includes machine-readable metadata and update checking. The catalogue entries are the skills and related tools that agents install and use.
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 alchaincyf/huashu-skills --skill huashu-script-polishgit clone --depth 1 https://github.com/alchaincyf/huashu-skillsWrote 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/alchaincyf/huashu-skills/huashu-script-polish)<a href="https://agentmods.dev/skills/alchaincyf/huashu-skills/huashu-script-polish"><img src="https://agentmods.dev/badge/skills/alchaincyf/huashu-skills/huashu-script-polish/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/alchaincyf/huashu-skills/huashu-script-polish"><img src="https://agentmods.dev/badge/skills/alchaincyf/huashu-skills/huashu-script-polish.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
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 | $0.00061 | $0.00684 |
| Opus 5.5 | $0.00024 | $0.00274 |
| Sonnet 5.5 | $0.00012 | $0.00137 |
| Haiku 4.5 | $0.00006 | $0.00068 |
Grade A, and why
huashu-script-polish 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 1mo 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
视频脚本口语化审校
让视频脚本更适合实际录制，强化口语感，去掉书面语和AI味。
何时使用
- 脚本初稿完成后
- 用户说"审校脚本"、"太书面化"
- 需要让脚本更口语化
核心目标
- 去掉书面语，全面口语化
- 适合大声说出来（不卡顿）
- 像花生在镜头前说话
三遍审校（视频专用）
第一遍：内容审校
- 事实准确、演示可行
- 逻辑清晰、步骤连贯
- 时长合理（150-180字/分钟）
第二遍：口语化审校（核心）
删除书面语：
- ❌ "接下来我们将进行..." → ✅ "我们来..."
- ❌ "进行操作" → ✅ "点击"
- ❌ "实现功能" → ✅ "做到"
- ❌ "综上所述" → ✅ 直接总结
加入口语词：
- ✅ "其实"、"你看"、"这里"、"那么"
- ✅ "说实话"、"我之前"、"这个很关键"
适合说出来：
- 短句为主（不超过20字）
- 用句号断句，不用逗号连长句
- 大声读一遍，卡顿的地方重写
第三遍：演示标注
- 标注哪里切屏幕、哪里特写
- 检查节奏和停顿
- 模拟实际录制流程
口语化改写示例
❌ 书面语：
接下来我们将进行Claude Code的安装操作。首先，打开终端，然后输入相应的命令...
✅ 口语化：
好，我们来装Claude Code。很简单，打开终端，输入这个命令...（切屏幕）你看，就这样。
参考资源
/写作参考/AI味审校指南.md- AI味审校（通用）/视频创作/_srt/- 花生历史视频字幕（学习风格）/写作参考/个人素材库/- 真实表达素材
最后更新: 2025-11-07
花叔出品 | AI Native Coder · 独立开发者 公众号「花叔」| 30万+粉丝 | AI工具与效率提升 代表作：小猫补光灯（AppStore付费榜Top1）·《一本书玩转DeepSeek》
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.
- 1mo ago First seen · 73 lines · 61 tokens per session scan A bc4f7d7f9f55
huashu-script-polish is a skill published in the GitHub repository alchaincyf/huashu-skills (2,025 stars, last pushed yesterday), licensed MIT. It adds 61 tokens to every session and 684 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
Other skills, from other repositories
claude-md-improver
Audit and improve CLAUDE.md files in repositories. Use when user asks to check, audit, update, improve, or fix CLAUDE.md files. Scans for all CLAUDE.md files, evaluates quality against templates, outputs quality report, then makes targeted updates. Also use when the user mentions "CLAUDE.md maintenance" or "project…
agent-platform-model-registry
Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.
gke-workload-security
Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running security audits (auditcluster.sh), enforcing Network Policies (default-deny and Dataplane V2 logging), isolating high-risk pods inside GKE Sandbox (gVisor), enforcing Pod…
gke-reliability
Improves GKE workload reliability, using PDBs, health probes, and topology spread constraints. Use when configuring GKE workload reliability, setting up PDBs, or configuring GKE health probes (liveness, readiness, startup). Don't use for generating K8s YAML manifests (use gke-manifest-generation) or disaster recovery…
google-cloud-solution-agentic-analytics-spark-knowledge-catalog
Discovers requirements and designs an end-to-end governed agentic analytics solution using Knowledge Catalog and Managed Service for Apache Spark (Lightning Engine). Use when designing data science and analytics workflows across structured and unstructured distributed data (including in S3, Azure Blob, AlloyDB, and…
glance-canonical-layouts
Use this skill to create home screen widgets using Jetpack Glance Canonical Layouts from the Android Platform Samples project, or when asked to implement standard widget layout patterns (including Check List, Image Grid, Snap Scrolling, and Standard Toolbar).