stock-watcher

agentbay-ai/agentbay-skills · updated May 2, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/agentbay-ai/agentbay-skills --skill stock-watcher
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summary

Personal stock watchlist management with real-time performance tracking from 10jqka.com.cn.

  • Add, remove, list, and clear stocks using 6-digit stock codes; data persists in a local watchlist file
  • Fetches live market data including price changes, performance metrics, and direct links to detailed stock pages
  • Supports A-share markets (Shanghai, Shenzhen, and STAR Board) with automatic error handling and rate limiting
  • Built-in performance summary command displays key metrics for all wa
skill.md

Stock Watcher Skill

This skill provides comprehensive stock watchlist management capabilities, allowing users to track their favorite stocks and get performance summaries using real-time data from 同花顺 (10jqka.com.cn).

自选股行情查看

当你要求查看自选股行情时,系统会直接显示以下信息:

  • 每只股票的代码和名称
  • 近期表现指标(涨跌幅等关键数据)
  • 详细信息链接(可点击查看)

无需额外命令,直接为你呈现简洁明了的行情概览。

管理自选股

添加股票

使用股票代码(6位数字)添加到自选股:

  • 例如:添加 600053 九鼎投资

删除股票

通过股票代码删除自选股:

  • 例如:删除 600053

查看自选股列表

显示当前所有自选股的完整列表

清空自选股列表

完全清空所有自选股

数据来源

主要使用同花顺 (10jqka.com.cn) 作为数据源:

  • 股票页面: https://stockpage.10jqka.com.cn/{stock_code}/
  • 支持沪深A股及科创板市场
  • 提供实时行情、技术分析和资金流向数据

自选股管理

文件格式

自选股存储在 ~/.clawdbot/stock_watcher/watchlist.txt

600053|九鼎投资
600018|上港集团
688785|恒运昌

支持操作

  1. 添加股票: 验证股票代码格式并添加到自选股
  2. 删除股票: 按股票代码精确匹配删除
  3. 查看列表: 显示当前自选股
  4. 清空列表: 完全清空自选股
  5. 行情总结: 获取所有股票的最新数据并提供简洁摘要

行情摘要特点

  • 直接显示关键行情指标,无冗余信息
  • 提供股票详情链接便于深入查看
  • 自动处理网络错误和数据异常
  • 合理控制请求频率(每秒1次)

注意事项

  • 股票代码格式: 使用6位数字代码(如 600053
  • 数据延迟: 行情可能有1-3分钟延迟
  • 网络依赖: 需要网络连接获取实时数据
  • 市场范围: 主要支持A股市场(沪市/深市/科创板)

安装与卸载

安装

运行 scripts/install.sh 脚本自动创建必要的目录结构。

卸载

运行 scripts/uninstall.sh 脚本完全移除所有相关文件。

脚本说明

所有脚本都使用统一的配置文件 config.py 来管理存储路径,确保路径一致性:

  • add_stock.py - 添加股票到自选股
  • remove_stock.py - 从自选股删除股票
  • list_stocks.py - 列出所有自选股
  • clear_watchlist.py - 清空自选股列表
  • summarize_performance.py - 获取股票行情摘要
how to use stock-watcher

How to use stock-watcher on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add stock-watcher
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/agentbay-ai/agentbay-skills --skill stock-watcher

The skills CLI fetches stock-watcher from GitHub repository agentbay-ai/agentbay-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/stock-watcher

Reload or restart Cursor to activate stock-watcher. Access the skill through slash commands (e.g., /stock-watcher) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.745 reviews
  • Sophia Shah· Dec 20, 2024

    We added stock-watcher from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Valentina Huang· Dec 12, 2024

    stock-watcher reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Ava Abebe· Dec 12, 2024

    Useful defaults in stock-watcher — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Chaitanya Patil· Dec 8, 2024

    Registry listing for stock-watcher matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Piyush G· Nov 27, 2024

    stock-watcher reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Benjamin Gupta· Nov 27, 2024

    Registry listing for stock-watcher matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Aanya Gonzalez· Nov 19, 2024

    stock-watcher is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Omar Tandon· Nov 11, 2024

    Keeps context tight: stock-watcher is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Shikha Mishra· Oct 18, 2024

    I recommend stock-watcher for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Meera White· Oct 18, 2024

    stock-watcher fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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