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 stock_research_memo_writer_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/stock_research_memo_writer_skill)<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/stock_research_memo_writer_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/stock_research_memo_writer_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/stock_research_memo_writer_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/stock_research_memo_writer_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 | $0.00066 | $0.01200 |
| Opus 5.5 | $0.00026 | $0.00480 |
| Sonnet 5.5 | $0.00013 | $0.00240 |
| Haiku 4.5 | $0.00007 | $0.00120 |
Grade A, and why
stock_research_memo_writer_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
Stock Research Memo Writer 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
本技能用于把分散的个股研究结果整理成一份结构清晰、便于分享和复用的研究备忘录。输出重点不是单纯罗列资料,而是沉淀“结论、依据、分歧、风险、后续跟踪”这五个最关键部分,让团队成员能快速接手和继续推进研究。
执行流程
Step 1:确认备忘录用途与深度
先明确这份备忘录是用于:
- 首次研究后的阶段性总结
- 晨会、周会或内部分享
- 为后续深挖建立统一底稿
若用户未指定,默认按“供团队内部快速理解并继续跟踪”的标准撰写。
Step 2:提炼核心投资结论
先把最想表达的结论压缩成几句清楚的话:
- 为什么值得关注
- 当前最大机会来自哪里
- 当前最大风险是什么
- 现阶段更适合行动、观察还是继续研究
结论部分应先于材料堆叠出现。
Step 3:整理支撑结论的事实与逻辑
围绕结论抽取真正重要的依据,包括:
- 业务模式与核心变量
- 经营与财务表现
- 行业与竞争位置
- 市场预期与估值位置
不要把所有搜到的内容全部塞进备忘录,只保留能支撑结论的关键材料。
Step 4:把核心分歧写清楚
一份有用的研究备忘录,必须说明:
- 市场为什么会同意这个观点
- 市场为什么可能不同意
- 哪个变量最可能让结论被证伪
这一步能让备忘录真正具备讨论价值,而不是单向陈述。
Step 5:补齐风险与跟踪清单
除了结论本身,还要列出:
- 当前结论最依赖的假设
- 需要持续跟踪的事件与指标
- 哪些信号一旦出现,应当更新或撤销观点
这样备忘录才能从“静态总结”升级为“动态研究底稿”。
Step 6:整理成标准化成稿
最终以统一结构输出,保证不同个股之间的备忘录可以横向比较、持续更新、团队复用。正文只呈现成稿,不展示内部整理过程。
输出结构
{股票名称}研究备忘录({YYYY-MM-DD})
一、结论摘要
- 当前结论:{看多 / 中性 / 谨慎 / 继续观察}
- 一句话理由:{说明}
- 最重要的验证变量:{变量}
二、公司与逻辑概览
- 公司在做什么:{一句话}
- 当前值得看的逻辑:{一句话}
- 最主要的争议点:{一句话}
三、支撑依据
| 维度 | 关键内容 | 对结论的意义 |
|---|---|---|
| 业务 | {描述} | {说明} |
| 财务 | {描述} | {说明} |
| 行业/竞争 | {描述} | {说明} |
| 估值 | {描述} | {说明} |
四、多空分歧
看多理由
- {理由 1}
- {理由 2}
看空理由
- {理由 1}
- {理由 2}
五、风险与失效条件
- {风险 1}
- {风险 2}
- {结论失效条件}
六、后续跟踪清单
- {跟踪项 1}
- {跟踪项 2}
- {跟踪项 3}
七、当前动作建议
- 建议动作:{继续跟踪 / 深入研究 / 等待验证 / 暂不行动}
- 原因:{说明}
质量要求
- 备忘录必须先给结论,再给依据,不能让读者自己从材料堆里猜结论。
- 所有内容都应服务后续复用,避免写成一次性聊天记录。
- 多空分歧与风险不能省略,否则备忘录缺乏讨论价值。
- 若数据或信息有缺口,应在跟踪清单中明确补齐方向。
- 文本风格应压缩、清晰、可传递,适合内部分享与持续更新。
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 · 143 lines · 66 tokens per session scan A fdd7f2905637
stock_research_memo_writer_skill is a skill published in the GitHub repository chuancyzhang/deepseek-cowork (18 stars, last pushed today), licensed Apache-2.0. It adds 66 tokens to every session and 1,200 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 2026-09-04.
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