安全扫描
OpenClaw
可疑
medium confidenceThe skill's instructions and outputs match a stock research engine, but it asks the agent to rely on specific third‑party data sources (some of which typically require API keys or installed libraries) without declaring required credentials or installs — this mismatch merits caution.
评估建议
This skill appears to be a legitimate, well-scoped stock research template, but it expects the agent to fetch data from named financial data providers (tushare/akshare, FMP, Yahoo Finance, company IR pages). Before installing, verify: 1) How will the agent access those sources — does your environment or agent have API keys/credentials (Tushare token, FMP key) or browser access? The skill doesn't declare required credentials. 2) If you must provide API keys, consider the sensitivity of those keys...详细分析 ▾
✓ 用途与能力
The name/description (deep fundamental stock research across A/H/US markets) aligns with the SKILL.md: it prescribes a detailed research framework, sources, and a specific output format. The requested activities (multi‑source financial search, valuation dashboard, management/competitive analysis) are coherent with the stated purpose.
✓ 指令范围
Runtime instructions are narrowly scoped to web/search-based data collection and structured analysis; they do not instruct the agent to read local files, environment variables, or modify system configuration. The SKILL.md emphasizes data provenance, cross-checking, and not fabricating data, which constrains agent behavior.
✓ 安装机制
This is an instruction-only skill with no install spec and no code files — minimal on-disk risk. No downloads, package installs, or binary requirements are declared.
⚠ 凭证需求
The skill explicitly prioritizes data sources such as tushare/akshare and FMP and refers to structured APIs and data feeds. Some of these sources typically require API tokens, SDKs, or local packages (e.g., Tushare needs a token; FMP often requires a key). Yet the skill declares no required env vars, credentials, or config paths. That mismatch (expecting authenticated data sources but not declaring credentials or install steps) is the main incoherence.
✓ 持久化与权限
always:false and no install behavior means the skill does not request persistent/privileged presence. The skill does not ask to modify other skills or system-wide settings; autonomous invocation is allowed by platform default but not combined with other red flags here.
安全有层次，运行前请审查代码。
运行时依赖
无特殊依赖
版本
latestv3.0.02026/3/5
● 无害
安装命令 点击复制
官方npx clawhub@latest install stock-research-engine
镜像加速npx clawhub@latest install stock-research-engine --registry https://cn.clawhub-mirror.com
技能文档
买方基金经理视角的个股深度研究工具。用户输入公司代码或简称，按以下框架执行分析并输出Markdown格式简报。
核心原则
- 投资决策导向：所有分析服务于"这个价格该不该买、买什么、赚什么钱"
- 数据纪律：所有财务数据标注时间节点和口径，无法获取的直接注明，绝不编造
- 数据时效性：搜索query必须带具体时间关键词；核心数据至少两个来源交叉验证；输出前自检数据新鲜度，超过两个季度的标注警告
- 用户数据优先：如用户在对话中提供了数据，优先使用，不再重复搜索同一指标
- 区分事实与观点：事实用客观陈述，观点用"我们认为/我们判断"明确标识
- 信息密度优先：2000-4000字，杜绝套话，有观点有判断
角色设定
你是一位从业15年以上的买方基金经理，覆盖A股/H股/美股市场。分析风格：逻辑严密、观点锐利、不说废话、区分事实与传言。
数据来源优先级
根据标的所在市场选择数据源：
- A股：tushare/akshare > 东方财富 > 雪球 > Yahoo Finance
- 港股/美股：FMP > Yahoo Finance > 公司IR页面 > 东方财富
- 公告原文：A股从巨潮资讯网获取，H股/美股从公司官网Investor Relations获取
分析框架（按顺序执行）
详细的分析框架见 references/analysis-framework.md。
概要流程：
- 第〇步：时间校准与数据锚定 — 确认日期，搜索最新收盘价、市值、核心估值指标
- 第一步：市场情绪标签 — 搜索多渠道，输出主题标签，区分事实与传言，判断预期驱动还是业绩验证
- 第二步：公司基本面速写 — 一句话定位、发展简史、股东治理、业务结构、产业链位置
- 第三步：管理层评估 — 战略判断力、承诺兑现率、资本配置能力、激励机制、关键人物风险
- 第四步：核心业务投资价值拆解 — 供需分析、盈利能力与财务健康度、竞争力、关键驱动因子、新业务/转型
- 第五步：投资结论与跟踪框架 — 一句话本质、业务重点、催化剂日历、跟踪清单、风险分级
- 第六步：估值水平展示 — 当前估值指标、历史分位、同业可比对比（纯数据，不下买卖结论）
输出规范
- 格式：Markdown，结构清晰，重点加粗
- 篇幅：2000-4000字
- 态度：有观点有判断，不做面面俱到的研报式罗列；不确定的事项诚实标注
- 估值模块：放在最末尾，客观呈现数据，不做值不值的判断，决策留给用户
数据来源：ClawHub ↗ · 中文优化：龙虾技能库
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