stock_first_look_skill

stock_first_look_skill is a skill for Claude Code, Codex from chuancyzhang/deepseek-cowork. It costs 59 tokens per session (1,515 once invoked), scanned A, original, Apache-2.0.

A first-look research tool for building a basic understanding of a company and its stock. It covers the business, important measures, investor concerns, valuation, and main risks.

In plain words
What is it for?
It is for initial stock research, quick background checks, and screening possible investments.
Why use it?
It gives a structured starting point when the company is unfamiliar. It helps decide whether a stock deserves deeper research before much time is spent on it.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It is for initial stock research, quick background checks, and screening possible investments.

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Install with agentmods
npx agentmods add skills/chuancyzhang/deepseek-cowork/stock_first_look_skill
Install

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.

Any agent
npx skills add chuancyzhang/deepseek-cowork --skill stock_first_look_skill
Clone the repo
git clone --depth 1 https://github.com/chuancyzhang/deepseek-cowork

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for stock_first_look_skill

README.md
[![agentmods](https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/stock_first_look_skill/github.svg)](https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/stock_first_look_skill)
Your own site
<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/stock_first_look_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/stock_first_look_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.

agentmods 80×15 button for stock_first_look_skill

Your own site · 80×15
<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/stock_first_look_skill"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/stock_first_look_skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 59 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,515 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00059 $0.01515
Opus 5.5 $0.00024 $0.00606
Sonnet 5.5 $0.00012 $0.00303
Haiku 4.5 $0.00006 $0.00152

Measured 1mo ago against content hash be1750341377, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

stock_first_look_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.

ai_skills/wind-aifinmarket/skills/stock_first_look_skill/SKILL.md · 155 lines

How it starts

The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Stock First Look 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

本技能用于在尽可能短的时间内,帮助使用者对一只陌生股票建立“够用且可讨论”的第一层认知。输出重点不是全面尽调,而是先回答五个问题:公司做什么、为什么值得看、市场在争论什么、当前大致贵不贵、继续研究前该先补哪几块信息。

执行流程

Step 1:确认分析对象与研究上下文

先确认股票名称、代码、上市地与所属行业,并识别用户此时的真实目的:

  • 是第一次接触,想快速建立基础认知
  • 还是已有关注,只想判断是否值得深入
  • 是用于自用判断,还是用于向团队口头汇报

若用户没有给出明确目标,默认按“第一次研究一只股票并判断是否值得继续跟进”的场景展开。

Step 2:提炼公司最核心的基础事实

先把最基础且最必要的信息压缩成短摘要,重点包括:

  • 公司主要卖什么产品或服务
  • 主要客户是谁
  • 主要收入和利润来自哪些业务模块
  • 所处产业链位置与行业属性
  • 近阶段最重要的经营或市场变化

这一阶段不追求完整历史沿革,只保留理解当前股票所需的最小信息集合。

Step 3:建立“为什么现在值得看”的判断框架

围绕当前时点提炼这只股票的关注理由,常见来源包括:

  • 财报、公告、政策、产品、订单、资本运作等事件催化
  • 行业景气、主题热度、板块轮动带来的关注提升
  • 业绩、估值、市场预期之间出现明显预期差
  • 股价位置、交易活跃度或市场讨论度突然变化

若没有明显催化,也要明确说明“目前没有强催化,主要属于观察名单而非优先研究对象”。

Step 4:提炼关键经营变量与基础财务快照

从业务模式出发,抓 3-5 个最重要的经营变量,并用有限的关键指标说明公司当前状态。优先关注:

  • 收入、利润、利润率、现金流等基础质量
  • 增长速度与增长结构
  • 业务分部或核心产品线表现
  • 对估值和股价最敏感的单一变量

若部分数据缺失,需明确标注,不用模糊描述替代。

Step 5:给出估值位置与市场分歧的初步判断

结合当前估值水平、历史区间、行业对比和市场情绪,判断公司大致处于:

  • 明显被低估、合理定价或偏高定价
  • 市场预期保守、均衡或过热
  • 估值弹性主要来自业绩兑现、逻辑重估还是情绪扩散

同时简要列出最重要的看多与看空变量,帮助使用者避免一上来就陷入单边叙事。

Step 6:形成“是否继续研究”的落地建议

在基础认知之上,明确回答三个问题:

  • 这只股票现阶段值不值得继续看
  • 若继续研究,下一步最该补哪几个问题
  • 若暂时不继续,原因究竟是信息不足、逻辑不清,还是赔率不佳

最终输出只呈现成稿,不展示中间检索路径或内部草稿。

输出结构


{股票名称}初识个股({YYYY-MM-DD})

一、30 秒结论

  • 这家公司做什么:{一句话}
  • 现在为什么值得看:{一句话}
  • 当前最大争议:{一句话}
  • 是否建议继续研究:{继续 / 暂缓 / 仅观察}

二、公司基础认知

维度 内容
主营业务 {一句话概述}
主要客户/市场 {一句话概述}
产业链位置 {一句话概述}
核心赚钱方式 {一句话概述}

三、当前最重要的 3 个关注点

  • 关注点 1:{内容}
  • 关注点 2:{内容}
  • 关注点 3:{内容}

四、关键经营与财务快照

指标 当前情况 解读
{指标1} {数值或描述} {说明}
{指标2} {数值或描述} {说明}
{指标3} {数值或描述} {说明}

五、估值与预期差判断

  • 估值位置:{偏低 / 合理 / 偏高 + 简述}
  • 市场预期:{保守 / 中性 / 偏热 + 简述}
  • 可能的重估触发:{事件或变量}

六、多空要点

看多逻辑

  • {要点 1}
  • {要点 2}

看空逻辑

  • {要点 1}
  • {要点 2}

七、下一步研究清单

  • {最该补的研究问题 1}
  • {最该补的研究问题 2}
  • {最该补的研究问题 3}

Read the full file on GitHub · 155 lines

Changes

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.

  1. 1mo ago First seen · 155 lines · 59 tokens per session scan A be1750341377

Subscribe to this mod's changes

stock_first_look_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 1,515 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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