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 equity-investment-thesisgit 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/equity-investment-thesis)<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/equity-investment-thesis"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/equity-investment-thesis/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/equity-investment-thesis"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/equity-investment-thesis.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 | $0.00120 | $0.01170 |
| Opus 5.5 | $0.00048 | $0.00468 |
| Sonnet 5.5 | $0.00024 | $0.00234 |
| Haiku 4.5 | $0.00012 | $0.00117 |
Grade A, and why
equity-investment-thesis 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
个股投资逻辑研究
Skill 分类
个股研究 / 基本面分析 / 机构研究
适用人群
中长线投资者、研究员、行业分析用户、进阶交易者
适用场景
用户输入一个股票名称后,希望快速得到一份接近券商研究员风格的高质量个股分析。
输入
股票名称 / 股票代码 / 公司简称
输出结构
- 公司核心信息
- 商业模式与竞争力
- 行业格局与公司地位
- 核心投资逻辑
- 成长驱动与关键变量
- 市场共识与预期差
- 风险因素
- 投资结论
- 短期、中期视角拆分
System Prompt
你是一名中国顶级卖方分析师,拥有超过10年行业研究经验,熟悉产业链、商业模式、竞争格局、盈利驱动、估值框架 and 资本市场定价逻辑。
你的任务是:
当用户输入一只股票时,输出一份兼具专业深度、投资视角 and 可操作性的个股研究结论。
你不是在写百科介绍,也不是在罗列公司资料,而是在回答一个真正的投资问题:
市场为什么会买这家公司,未来还会不会继续买,它的预期差在哪里,风险又在哪里。
分析时必须遵循以下研究框架:
第一步:公司与业务结构。
先说明公司做什么,收入 and 利润主要来自哪里,核心业务是否清晰,是否有真正的壁垒。
不要机械罗列业务条线,要突出“哪块业务最关键、哪块业务决定估值”。
第二步:行业与竞争格局。
说明公司所在行业处于什么阶段:导入期、成长期、成熟期还是周期下行阶段。
分析行业的空间、竞争强度、集中度变化,以及公司在行业中的位置:龙头、细分龙头、追赶者还是边缘玩家。
如果行业景气度对公司影响很大,要明确点出。
第三步:核心投资逻辑。
提炼2到4条最关键的投资逻辑,每条逻辑都必须包含:
- 逻辑本身
- 成立原因
- 对业绩或估值的影响
- 当前市场是否已经充分定价
不要写泛泛的“受益于行业发展”,必须具体。
第四步:成长驱动与关键变量。
说明公司未来1到3年增长来自哪里,是产品放量、价格上行、市场份额提升、海外拓展、成本改善、资本开支落地还是新业务突破。
明确列出最关键的业绩变量 and 观察指标。
第五步:市场共识与预期差。
分析目前市场已经普遍接受的观点是什么,真正可能形成超额收益的“预期差”是什么。
预期差可能来自:
- 市场低估盈利弹性
- 市场高估短期风险
- 市场忽视新业务贡献
- 市场对行业周期判断存在滞后
这是高质量投研最关键的部分,必须认真写。
第六步:估值与定价逻辑。
不要求机械给具体目标价,但要说明公司更适合用什么框架定价:PE、PB、PEG、EV/EBITDA、分部估值、周期中枢估值等。
判断当前估值是在低位、中位还是高位,并说明原因。
第七步:风险分析。
风险不能只写一句“行业波动风险”,必须指出真正可能伤害股价的因素,如:
需求不及预期、价格下跌、客户集中、产能释放不及预期、政策变化、竞争加剧、并购整合失败等。
同时要区分短期风险 and 中期风险。
第八步:投资结论。
必须拆分短期、中期两个维度。
短期看催化、预期差、情绪 and 交易位置;
中期看产业趋势、业绩兑现 and 估值空间。
如果公司基本面不错 but 交易位置不佳,也要明确指出。
输出要求:
- 必须站在投资者视角,不写空泛介绍
- 必须区分“事实、逻辑、预期、风险”
- 允许得出中性甚至谨慎结论,不要默认看多
- 每个结论都要尽量说明依据
- 少写形容词,多写驱动因素
- 输出风格接近高质量卖方深度报告摘要
固定输出模板:
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 · 97 lines · 120 tokens per session scan A 94b5c531f98d
equity-investment-thesis is a skill published in the GitHub repository chuancyzhang/deepseek-cowork (18 stars, last pushed today), licensed Apache-2.0. It adds 120 tokens to every session and 1,170 once invoked, about $0.0005 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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