本技能提供强大的股票数据查询与分析能力,主要包含:
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionopenclaw-stock-skillExecute the skills CLI command in your project's root directory to begin installation:
Fetches openclaw-stock-skill from 1018466411/openclaw-stock-data-skill and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate openclaw-stock-skill. Access via /openclaw-stock-skill in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
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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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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本技能提供强大的股票数据查询与分析能力,主要包含:
npx skills add https://github.com/1018466411/openclaw-stock-data-skill
安装时按提示选择:
本技能教会代理如何使用你自建的股票数据服务(注册账号 https://data.diemeng.chat),通过 API Key 进行鉴权,查询股票的日线、分钟线、财务指标等数据。
⚙️ API Key 配置约定
- OpenClaw 会按照
skills.entries.<key>配置 把 API Key 和自定义配置注入到进程环境变量中。- 本技能约定使用环境变量
STOCK_API_KEY作为主密钥,并在metadata.openclaw.primaryEnv中声明,以便通过skills.entries.openclaw-stock-skill.apiKey统一配置。- 推荐的 OpenClaw 配置示例(
~/.openclaw/openclaw.json):{ skills: { entries: { "openclaw-stock-skill": { enabled: true, // 建议在 OpenClaw UI 的 Skill 参数面板里填写 apiKey, // Gateway 会自动将其写入 STOCK_API_KEY 环境变量 apiKey: { source: "env", provider: "default", id: "STOCK_API_KEY" }, env: { // 可在这里直接写死,或通过系统环境变量覆盖 STOCK_API_KEY: "YOUR_REAL_STOCK_API_KEY" }, config: { // 可选:覆盖默认域名 baseUrl: "https://data.diemeng.chat" } } } } }参考文档:Skills Config、Skills
如果 API 返回 403 错误,说明您的账号没有开通对应接口的权限。 请务必访问官网 https://data.diemeng.chat/,在个人中心开通所需权限(如股票行情、实时快照、可转债等)。
get_stock_snapshot_daily(不传日期或传今日):获取最新实时快照(价格、成交量、五档盘口等)。get_stock_snapshot_push_history:获取实时推送的历史记录。get_call_auction:获取集合竞价数据。get_daily_data:获取历史日 K 线。get_history_data:获取历史分钟线。get_finance_data:获取历史财务指标。get_stock_snapshot_daily(传历史日期):获取历史快照。get_index_history:获取指数分钟级历史数据。get_ths_sector_categories:获取同花顺板块分类数据。get_ths_constituent_stocks:获取同花顺成分股数据。https://data.diemeng.chat,如存在 skills.entries.openclaw-stock-skill.config.baseUrl 则优先使用配置中的 baseUrl。apiKey: <STOCK_API_KEY>(推荐)X-API-Key: <STOCK_API_KEY>apiKey 字段,但为了安全与规范,本技能统一通过 Header 传递。{ "code": 200, "msg": "成功", "data": { ... } }DataAccessVerifier 实现)。代理应将本技能视作一组 HTTP 能力,而不是单一接口:
代理在规划调用时,应根据用户自然语言意图,选择以上能力并组合使用。
POST /api/stock/daily{baseUrl}/api/stock/dailyPOSTContent-Type: application/jsonapiKey: <STOCK_API_KEY>DailyDataRequest):{
"stock_code": "000001.SZ",
"start_time": "2024-01-01",
"end_time": "2024-01-31",
"page": 0,
"page_size": 1000
}
stock_code 可以是单个字符串,也可以是字符串数组。start_time、end_time 格式为 YYYY-MM-DD。page 从 0 开始。data.total:总记录数data.list:每条记录包含 stock_code, stock_name, trade_date, open, high, low, close, vol, amount 等字段,价格与成交量已在后端统一保留 2 位小数。data.total:总记录数data.list:每条记录包含 stock_code, trade_date, open, high, low, close, vol, amount 等字段,价格与成交量已在后端统一保留 2 位小数。代理在需要“某股某段时间的日 K 线”时,应优先选择该接口。
POST /api/stock/history{baseUrl}/api/stock/historyPOSTHistoryDataRequest):{
"stock_code": "000001.SZ",
"level": "5min",
"start_time": "2024-01-01 09:30:00",
"end_time": "2024-01-01 15:00:00",
"page": 0,
"page_size": 1000
}
level:"1min" | "5min" | "15min" | "30min" | "60min"start_time / end_time:
YYYY-MM-DD HH:MM:SSdata.list 中每条包含:stock_code, trade_time, open, high, low, close, vol, amount。用于用户询问“某天/某段时间内的分钟级行情、分时数据”等场景。
POST /api/realtime/history{baseUrl}/api/realtime/historyPOST{
"stock_code": "000001.SZ",
"trade_time": "2026-03-15 09:31:00"
}
stock_code 或 trade_time 至少提供一个。stock_code + trade_time 进行去重。调用建议(定时任务拉取全市场数据):
- 建议使用时间 (
trade_time) 来获取实时分时,一次可以获取某一分钟的全市场数据。- 使用定时任务来获取数据,每分钟获取上一分钟的数据。
- 建议在每分钟的 2 到 5 秒后开始获取。
- 如果获取不到,建议暂停 1 秒后继续获取,最多重试不要超过 60 次,避免陷入死循环。
- 建议在每分钟 15 秒之后再调用接口更新一次数据,确保数据的准确性。
POST /api/stock/finance{baseUrl}/api/stock/financePOSTFinanceDataRequest):{
"stock_code": "000001.SZ",
"start_time": "2024-01-01",
"end_time": "2024-03-31",
"page": 0,
"page_size": 1000
}
stock_code, stock_name, trade_date, close, turnover_rate, turnover_rate_f, volume_ratio, pe, pe_ttm, pb, ps, ps_ttm, dv_ratio, dv_ttm, total_share, float_share, free_share, total_mv, circ_mv 等。适合估值分析、换手率、成交金额、市值等相关问题。
GET /api/stock/list{baseUrl}/api/stock/listGETstock_code(可选):精确股票代码筛选page:默认 0page_size:默认 20000success 结构中):
data.totaldata.list:包含 stock_code, name, area, industry, list_date, symbol, list_status, delist_date, is_hs 等。当用户只给出股票名称、地区、行业等描述时,可先通过该接口获取匹配列表,再提示用户选择具体代码。
GET /api/basic/calendar & GET /api/basic/snapshotGET /api/basic/calendar{baseUrl}/api/basic/calendarGETstart_time: YYYY-MM-DDend_time: YYYY-MM-DDdata 为数组,每条含 date, is_open(1 为交易日,0 为休市)。当用户问“某段时间哪些是交易日”“下一个交易日是什么时候”等,可使用此接口。
GET /api/basic/snapshot{baseUrl}/api/basic/snapshotGETstock_code(可选)page, page_size当用户需要“当前(最近一次)盘口快照”或大盘扫描时,可使用此接口。
POST /api/stock/search{baseUrl}/api/stock/searchPOSTContent-Type: application/jsonapiKey: <STOCK_API_KEY>{
"query": "pe_ttm < 20 且 turnover_rate > 3%",
"stock_code": "000001.SZ",
"date": "2024-01-01",
"page": 0,
"page_size": 100,
"sort_by": "pe_ttm",
"sort_order": "asc"
}
字段说明:
query(必填):搜索条件,支持自然语言或表达式
pe_ttm < 20、turnover_rate > 3%、pe_ttm < 20 且 turnover_rate > 3%市盈率小于20、换手率大于3%circ_mv > 100亿、volume > 1000万stock_code(可选):精确股票代码筛选date(可选):日期,格式 YYYY-MM-DD 或 MM-DD(默认为当年)
stock_snapshot_daily(最新实时数据)stock_finance_daily(历史财务数据)page:页码,从 0 开始page_size:每页数量,最大 1000sort_by(可选):排序字段,如 pe_ttm、turnover_ratesort_order(可选):排序方向 asc 或 desc(默认 desc)支持的字段:
price / close:股价/收盘价pct_chg:涨跌幅turnover_rate:换手率pe / pe_ttm:市盈率pb:市净率total_mv / circ_mv:总市值/流通市值total_share / float_share:总股本/流通股本volume / turnover:成交量/成交额dividend_ratio:股息率响应主体:
data.total:总记录数data.list:符合条件的股票列表重要提醒:该接口单次请求最多返回 1000 条数据。如需获取更多结果,请使用分页功能。
适用场景:用户需要根据财务指标筛选股票,如"帮我找出 PE<20 的股票"、"换手率大于 5% 的股票有哪些"。
POST /api/stock/call_auction{baseUrl}/api/stock/call_auctionPOSTapiKey: <STOCK_API_KEY>{
"stock_code": "000001.SZ",
"start_time": "2024-01-01 09:15:00",
"end_time": "2024-01-01 09:25:00",
"page": 0,
"page_size": 100
}
start_time / end_time:时间范围,支持仅日期(自动补全时间)page_size:最大 10000stock_code, name, trade_time, close, open, high, low, pre_close, vol, amount, turnover_rate, pe, pb, pe_ttm, dv_ttm 等重要提醒:单次请求最多返回 10000 条数据。
POST /api/stock/closing_snapshot{baseUrl}/api/stock/closing_snapshotPOSTapiKey: <STOCK_API_KEY>✓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
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share 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
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
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4.5★★★★★57 reviews
SShikha Mishra★★★★★Dec 28, 2024I recommend openclaw-stock-skill for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
ZZara Flores★★★★★Dec 28, 2024openclaw-stock-skill reduced setup friction for our internal harness; good balance of opinion and flexibility.
AAmina Choi★★★★★Dec 20, 2024We added openclaw-stock-skill from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
AAmina Park★★★★★Dec 4, 2024openclaw-stock-skill has been reliable in day-to-day use. Documentation quality is above average for community skills.
IIsabella Garcia★★★★★Dec 4, 2024openclaw-stock-skill fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
TTariq Agarwal★★★★★Nov 23, 2024Solid pick for teams standardizing on skills: openclaw-stock-skill is focused, and the summary matches what you get after install.
TTariq Flores★★★★★Nov 23, 2024Registry listing for openclaw-stock-skill matched our evaluation — installs cleanly and behaves as described in the markdown.
YYash Thakker★★★★★Nov 19, 2024openclaw-stock-skill fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
MMeera Li★★★★★Nov 19, 2024We added openclaw-stock-skill from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
SSakshi Patil★★★★★Nov 11, 2024Useful defaults in openclaw-stock-skill — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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