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-researchgit 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-research)<a href="https://agentmods.dev/skills/alchaincyf/huashu-skills/huashu-research"><img src="https://agentmods.dev/badge/skills/alchaincyf/huashu-skills/huashu-research/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-research"><img src="https://agentmods.dev/badge/skills/alchaincyf/huashu-skills/huashu-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector 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 | $0.00065 | $0.00838 |
| Opus 5.5 | $0.00026 | $0.00335 |
| Sonnet 5.5 | $0.00013 | $0.00168 |
| Haiku 4.5 | $0.00006 | $0.00084 |
Grade A, and why
huashu-research 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
调研 Skill
结构化的网络调研流程，核心目标：调研成果实时持久化，防止会话截断丢失工作。
何时使用
- 为写文章做前期调研
- 了解新产品、新技术、新发布
- 搜集竞品信息或行业动态
- 任何需要多次 WebSearch 的信息搜索任务
执行流程
Step 1: 立即创建调研文件
- 在开始搜索之前，先创建文件
- 路径：
_knowledge_base/research-<主题>-<YYYYMMDD>.md - 初始内容包含：调研目标、关键问题、预期输出
# [主题] 调研笔记
调研日期：YYYY-MM-DD
调研目标：[一句话说明]
## 关键问题
1. [问题1]
2. [问题2]
3. [问题3]
## 发现
（调研中逐步填充）
## 来源列表
（每次搜索后追加）
Step 2: 搜索并增量保存
- 每次 WebSearch 后，立即将发现追加到文件
- 每条发现附上来源 URL 和日期
- 遵循信息源优先级（见 SHARED-RULES.md）
Step 3: 阶段摘要
- 每完成3次搜索，在文件中保存一次「阶段摘要」
- 格式：
### 阶段摘要 (第N轮)+ 当前关键发现
Step 4: 最终简报
调研结束时，整理文件为结构化简报：
## 调研结论
### 关键事实
1. [事实1]（来源：URL）
2. [事实2]（来源：URL）
### 来源列表
| 来源 | URL | 发布日期 | 可信度 |
|------|-----|---------|--------|
| ... | ... | ... | 高/中/低 |
### 待确认问题
- [还需要进一步验证的点]
### 写作建议
- [基于调研结果，对后续写作的建议]
关键原则
- 先建文件再搜索：确保第一次搜索结果就被保存
- 增量保存不等到最后：每次搜索后立即追加
- 调研和写作分离：本 Skill 只做调研，不开始写草稿
- 标注可信度：区分一手信息（官方）和二手信息（媒体/社区）
- 忽略过时信息源：知乎/百度（2025年前）、营销软文
与其他 Skill 的关系
- 调研完成后，用户可触发 /选题生成 来确定写作方向
- 调研文件将作为后续写作的输入素材
- 如果调研中发现的信息适合长期留存，保存到对应的 _knowledge_base 分类目录
输出位置
- 调研笔记：
_knowledge_base/research-<主题>-<YYYYMMDD>.md - 长期知识：
_knowledge_base/<分类>/<主题>-<YYYYMM>.md
最后更新: 2026-02-06
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 · 101 lines · 65 tokens per session scan A d2db5ef94c20
huashu-research is a skill published in the GitHub repository alchaincyf/huashu-skills (2,025 stars, last pushed yesterday), licensed MIT. It adds 65 tokens to every session and 838 once invoked, about $0.0003 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.
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