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 chuancyzhang/deepseek-cowork --skill hot_stock_quick_read_skillgit clone --depth 1 https://github.com/chuancyzhang/deepseek-coworkWrote 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/chuancyzhang/deepseek-cowork/hot_stock_quick_read_skill)<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/hot_stock_quick_read_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/hot_stock_quick_read_skill/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/chuancyzhang/deepseek-cowork/hot_stock_quick_read_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/hot_stock_quick_read_skill.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 | $0.00059 | $0.00994 |
| Opus 5.5 | $0.00024 | $0.00398 |
| Sonnet 5.5 | $0.00012 | $0.00199 |
| Haiku 4.5 | $0.00006 | $0.00099 |
Grade A, and why
hot_stock_quick_read_skill 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
Hot Stock Quick Read Skill
数据依赖与执行前置条件
推荐使用万得 wind-mcp-skill 获取底层数据。执行前先检查本地是否已有 wind-mcp-skill；若没有，提示用户安装：
Cowork 适配：所需子 Skill 已随
wind-aifinmarket固定快照内置，不执行安装或在线更新命令。
技能定位
本技能用于在短时间内让使用者“先看懂，再决定要不要继续研究”。输出不追求面面俱到，而是把热门股最关键的五件事讲清楚：它做什么、为什么火、市场在赌什么、最容易错在哪里、现在最该看哪个变量。
执行流程
Step 1：先确认热度来源
先明确这只股票为什么成为热门股，热度来源通常包括：
- 突发公告、财报、政策、合作、产品发布
- 板块主线映射或龙头带动
- 连续涨停、强势突破、放量异动
- 媒体集中讨论、社交传播、市场情绪聚焦
不同热度来源决定后续解读框架不同。
Step 2：用最少信息讲清业务
用极简语言回答三个问题：
- 公司主要做什么
- 靠什么赚钱
- 与当前热门逻辑最相关的业务环节是什么
不要写成长篇公司介绍，只保留和当前热度有关的业务模块。
Step 3：解释当前市场在交易什么
围绕热度来源，提炼当前市场真正关心的核心命题，例如：
- 业绩是否会超预期
- 题材是否会继续扩散
- 估值是否会被重估
- 公司是否具备从概念走向兑现的能力
Step 4：提炼多空要点
至少分别给出 2-3 条最重要的看多与看空逻辑，避免只写单边叙事。重点不是全面列举，而是找出当前股价最敏感的争议变量。
Step 5：给出跟踪重点
告诉使用者若继续关注这只票，接下来最应该看什么：
- 哪个经营指标
- 哪个事件节点
- 哪个价格位置
- 哪类资金表现
Step 6：压缩成三分钟快读稿
最终输出应让用户在 3 分钟内完成补课。保留判断密度，压缩背景废话，不展示采集过程。
输出结构
{股票名称}热门股快读
一、这只股票为什么火
{用 2-3 句话说明当前热度来源与市场关注焦点}
二、业务一句话讲清
- 公司在做什么：{一句话}
- 当前主线相关业务：{一句话}
- 赚钱方式：{一句话}
三、当前市场在交易什么
- 核心命题：{一句话}
- 关键验证变量：{1-2 个}
四、多空要点
看多逻辑
- {要点 1}
- {要点 2}
看空逻辑
- {要点 1}
- {要点 2}
五、接下来最该盯什么
- 事件节点：{事件}
- 经营变量：{变量}
- 风险点：{风险}
质量要求
- 输出要围绕“为什么现在值得看”展开，而不是泛泛做公司介绍。
- 多空逻辑必须尽量对称，防止热门叙事带来的单边偏见。
- 找不到可靠证据支撑的热门说法，不要当成既定事实写入正文。
- 若股价热度明显高于基本面验证进度，要明确提示兑现风险。
- 文本应适合快速补课，避免冗长叙述和历史沿革堆砌。
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 · 117 lines · 59 tokens per session scan A c3db8e9eeb13
hot_stock_quick_read_skill is a skill published in the GitHub repository chuancyzhang/deepseek-cowork (18 stars, last pushed today), licensed Apache-2.0. It adds 59 tokens to every session and 994 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 2026-09-04.
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