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 mx-datagit 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/mx-data)<a href="https://agentmods.dev/skills/chuancyzhang/deepseek-cowork/mx-data"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/mx-data/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/mx-data"><img src="https://agentmods.dev/badge/skills/chuancyzhang/deepseek-cowork/mx-data.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 | $0.00026 | $0.02961 |
| Opus 5.5 | $0.00010 | $0.01184 |
| Sonnet 5.5 | $0.00005 | $0.00592 |
| Haiku 4.5 | $0.00003 | $0.00296 |
Grade A, and why
mx-data 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.
How it starts
The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
mx-data 妙想金融数据 skill
Cowork 适配说明:
MX_APIKEY和MX_API_URL由能力中心统一配置;默认产物目录为当前会话工作区的mx_data/output。下文中的export、OpenClaw 固定路径和直接安装说明仅作为上游参考。
本 Skill 基于东方财富权威数据库及最新行情底层数据构建,支持通过自然语言查询以下三类数据:
- 行情类数据
股票、行业、板块、指数、基金、债券的实时行情、主力资金流向、估值等数据。 - 财务类数据
上市公司与非上市公司的基本信息、财务指标、高管信息、主营业务、股东结构、融资情况等数据。 - 关系与经营类数据
股票、非上市公司、股东及高管之间的关联关系数据,以及企业经营相关数据。
采用此skill可避免模型基于自身过时知识回答金融相关数据问题,可为大模型提供权威及时的金融数据。
配置
- API Key: 通过环境变量
MX_APIKEY设置 - 默认输出目录:
/root/.openclaw/workspace/mx_data/output/(自动创建) - 输出文件名前缀:
mx_data_ - 输出文件:
mx_data_{query}.xlsx- Excel 文件,每个数据表一个 sheet(多 sheet)mx_data_{query}_description.txt- 查询结果描述文件mx_data_{query}_raw.json- API 原始 JSON 数据
使用方式(直接 Python 脚本调用)
- 在妙想Skills页面获取apikey。(链接:https://dl.dfcfs.com/m/itc4)
- 将apikey存到环境变量,命名为MX_APIKEY:
export MX_APIKEY=your_apikey_here - 直接运行 Python 脚本查询,支持自然语言问句:
# ==================== 常用调用示例 ====================
# 1. 个股实时行情查询
python ./mx_data.py "东方财富最新价"
python ./mx_data.py "贵州茅台今日收盘价 涨跌幅"
python ./mx_data.py "宁德时代主力资金流向"
# 2. 历史行情数据查询
python ./mx_data.py "贵州茅台近五年年报收盘价"
python ./mx_data.py "比亚迪近一年每个交易日的开盘价收盘价成交量"
# 3. 财务数据查询
python ./mx_data.py "贵州茅台近三年净利润 营业收入"
python ./mx_data.py "东方财富每股收益 净资产收益率 近五年"
python ./mx_data.py "万科A资产负债率 毛利率 近三年"
# 4. 上市公司基本信息
python ./mx_data.py "比亚迪公司简介 主营业务 成立时间"
python ./mx_data.py "贵州茅台董事长是谁 总股本多少"
# 5. 股东信息
python ./mx_data.py "贵州茅台十大股东"
python ./mx_data.py "比亚迪机构持股比例"
# 6. 板块/指数行情
python ./mx_data.py "沪深300指数最新点位 涨跌幅"
python ./mx_data.py "新能源板块成分股平均涨跌幅"
# 7. 指定输出目录(可选)
python ./mx_data.py "贵州茅台近五年年报" /path/to/output
⚠️ 安全注意事项
- 外部请求: 本 Skill 会将您的查询文本发送至东方财富官方 API 域名 (
mkapi2.dfcfs.com) 以获取金融数据。- 凭据保护: API Key 仅通过环境变量
MX_APIKEY在服务端或受信任的运行环境中使用,不会在前端明文暴露。
数据限制说明
请谨慎查询大数据范围的数据,如某只股票3年的每日最新价,可能会导致返回内容过多,模型上下文爆炸问题。
输出说明
脚本执行后会:
- 在终端输出查询结果预览(前20行)
- 自动创建输出目录
/root/.openclaw/workspace/mx_data/output/ - 保存完整数据到 Excel 文件(多 sheet)
- 保存原始 JSON 响应供二次处理
- 保存描述文件记录查询条件和结果统计
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 199 lines · 26 tokens per session scan A 89a72be6b248
mx-data is a skill published in the GitHub repository chuancyzhang/deepseek-cowork (18 stars, last pushed today), licensed Apache-2.0. It adds 26 tokens to every session and 2,961 once invoked, about $0.0001 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 2026-08-30.
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