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 staruhub/ClaudeSkills --skill geek-skills-a-share-analystgit clone --depth 1 https://github.com/staruhub/ClaudeSkillsWrote 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/staruhub/claudeskills/geek-skills-a-share-analyst)<a href="https://agentmods.dev/skills/staruhub/claudeskills/geek-skills-a-share-analyst"><img src="https://agentmods.dev/badge/skills/staruhub/claudeskills/geek-skills-a-share-analyst/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/staruhub/claudeskills/geek-skills-a-share-analyst"><img src="https://agentmods.dev/badge/skills/staruhub/claudeskills/geek-skills-a-share-analyst.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00202 | $0.01943 |
| Opus 5 | $0.00101 | $0.00971 |
| Sonnet 5 | $0.00040 | $0.00389 |
| Haiku 4.5 | $0.00020 | $0.00194 |
Grade A, and why
a-share-analyst 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 13d 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
A股分析师 Skill
专业的A股市场分析工具,整合多数据源,提供技术面、基本面综合分析和智能选股策略。
数据获取
使用AKShare作为主要数据源(免费、开源、无需token):
pip install akshare --break-system-packages
核心数据获取示例
import akshare as ak
# 实时行情
df = ak.stock_zh_a_spot_em() # 全部A股实时行情
# 历史K线
df = ak.stock_zh_a_hist(symbol="000001", period="daily", adjust="qfq")
# 板块行情
df = ak.stock_board_concept_name_em() # 概念板块
df = ak.stock_board_industry_name_em() # 行业板块
# 龙虎榜(日期用实际查询区间,格式 YYYYMMDD)
df = ak.stock_lhb_detail_em(start_date="<起始日>", end_date="<结束日>")
# 资金流向
df = ak.stock_individual_fund_flow(stock="000001", market="sz")
分析工作流程
1. 每日盘前分析
执行顺序:
- 获取大盘指数(上证、深证、创业板)
- 分析板块热点轮动
- 筛选涨停股及连板股
- 检测北向资金流向
- 生成今日关注清单
2. 技术面分析
对单只股票执行:
- 获取历史K线数据(至少60日)
- 计算技术指标(见
references/technical_indicators.md) - 识别K线形态(见
references/candlestick_patterns.md) - 判断趋势和支撑/阻力位
- 生成技术面评分
3. 基本面分析
执行顺序:
- 获取财务数据(营收、净利润、ROE等)
- 计算估值指标(PE、PB、PS)
- 分析行业地位和竞争优势
- 评估成长性和安全边际
- 生成基本面评分
4. 智能选股策略
策略类型选择:
- 多因子综合策略 → 执行
scripts/strategy_multi_factor.py(已实现,内置 ST/停牌过滤) - 趋势突破 / 价值低估 / 动量因子等单因子策略 → 目前无独立脚本,在 multi_factor 基础上调整因子权重,或按需自行实现
输出格式
个股分析报告模板
# [股票名称]([股票代码]) 分析报告
## 基本信息
- 当前价格:¥XX.XX(涨跌幅 +X.XX%)
- 市值:XXX亿 | PE(TTM):XX.X | PB:X.XX
## 技术面分析
- 趋势判断:[上升/震荡/下降]
- 支撑位:¥XX.XX | 阻力位:¥XX.XX
- 技术指标:MACD [金叉/死叉] | KDJ [超买/超卖/中性] | RSI [XX]
## 基本面分析
- 营收增速:XX% | 净利润增速:XX%
- ROE:XX% | 毛利率:XX%
## 综合评分
- 技术面:⭐⭐⭐⭐☆ (4/5)
- 基本面:⭐⭐⭐☆☆ (3/5)
## 操作建议
[具体建议及风险提示]
每日选股清单模板
# 每日选股清单 [日期]
## 市场概览
- 上证指数:XXXX.XX(+X.XX%)
- 深证成指:XXXXX.XX(+X.XX%)
- 创业板指:XXXX.XX(+X.XX%)
## 热点板块 TOP5
1. [板块名称] +X.XX%
2. ...
## 精选个股
### 趋势突破型
| 代码 | 名称 | 现价 | 涨幅 | 突破形态 | 评分 |
|------|------|------|------|----------|------|
| ... | ... | ... | ... | ... | ... |
### 价值低估型
| 代码 | 名称 | 现价 | PE | PB | 评分 |
|------|------|------|-----|-----|------|
| ... | ... | ... | ... | ... | ... |
## 风险提示
投资有风险,以上分析仅供参考,不构成投资建议。
关键脚本
scripts/fetch_market_data.py- 市场数据获取scripts/technical_analysis.py- 技术指标计算(输出中性强弱描述,非买卖评级)scripts/strategy_multi_factor.py- 多因子选股(含 ST/停牌过滤)scripts/generate_report.py- 报告生成(需在 scripts/ 目录内运行,依赖 technical_analysis)
What ships with it
9 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.
- evals/routing-evals.json 1.6 KB
- references/candlestick_patterns.md 3.9 KB
- references/factor_library.md 6.7 KB
- references/fundamental_metrics.md 4.0 KB
- references/technical_indicators.md 4.0 KB
- scripts/fetch_market_data.py 4.1 KB runs code
- scripts/generate_report.py 8.3 KB runs code
- scripts/strategy_multi_factor.py 8.6 KB runs code
- scripts/technical_analysis.py 11 KB runs code
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.
- 13d ago First seen · 174 lines · 202 tokens per session scan A 22a808b5bb9a
a-share-analyst is a skill published in the GitHub repository staruhub/ClaudeSkills (712 stars, last pushed 1mo ago), licensed MIT. It adds 202 tokens to every session and 1,943 once invoked, about $0.0010 per session on Opus 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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